STUDY OF THIN-WALL INJECTION MOLDING
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate School of
The Ohio State University
By
Guojun Xu, M.E.
*****
The Ohio State University
2004
Dissertation Committee:
Approved by
Professor Kurt W. Koelling, Adviser
Professor L. James Lee
Professor Jose M. Castro
Adviser
Department of Chemical Engineering
ABSTRACT
Thin-wall injection molding has received increasing attention over the past few
years due to economic and environmental concerns. However, due to the difficulties
encountered in the thin-wall molding process, systematic investigation is lacking in
machine performance, mold design/manufacture requirement, molding characteristics,
computer aided engineering (CAE) simulation, part quality and part design criteria.
Furthermore, the combination of viscoelastic materials, complex molding geometry and
cyclic processing conditions has generated some problems, such as flow marks, polymer
degradation, sink marks and warpage, under high-speed and high-pressure injection
molding. So it is very important to design, operate, and control thin-wall molding
optimally to guarantee part quality as well as reduce cost.
In this study, alternate and synchronous dull and glossy flow marks, two surface
quality problems, were studied. For the alternate flow marks, the effect of polymer
rheology, mold geometry, operating variables, and mold surface coatings on the
appearance of the flow marks was studied. The flow marks occurred above a critical
wall shear stress, but disappeared at high injection speeds. Mold geometry and mold
temperature were found to affect the wavelength and the width of the flow marks, while
melt temperature did not have much effect. Slip was not the cause of the generation of
ii
the alternate flow marks. For synchronous dull and glossy flow marks, the effect of
operating parameters, mold geometry, and mold surface coatings on the flow marks was
studied. The flow marks occurred above a certain flow front velocity, but were less
visible as the mold temperature was increased. It was also found that mold surface
coatings did not eliminate the flow marks. The generation of these flow marks was
explained by an entry viscoelastic flow instability.
Furthermore, thin-wall injection molding with micro-features was investigated.
The filling length in microchannels was measured and compared with simulation. The
heat transfer coefficient was found to be very sensitive to the filling length prediction. In
order to investigate the effect of input properties on the simulation output, mold cavity
pressure was studied. The goal was to understand the effect of pressure-dependent
viscosity, heat capacity, heat transfer coefficient, juncture pressure loss and pvT-data on
cavity pressure and pressure drop prediction, and evaluate the importance of each
parameter. The cavity pressure and pressure drop were measured experimentally and
compared. Furthermore, the method to improve the prediction accuracy was discussed
to help design and predict.
As the increasing use of plastics, the plastics waste has become a main concern.
The final part of the research focuses on the mechanical and rheological properties of
virgin and recycled high impact polystyrene materials. In this study, we describe our
progress in evaluating the viability of reusing post-consumer and virgin polymer blends
of HIPS from electronics equipment housings. Plastics reuse challenges are briefly
reviewed, and experimental results, such as rheological properties, mechanical
iii
properties, molecular weight and morphology of different blends, are summarized and
discussed for reuse of HIPS. Finally, the study introduces a new approach to determine
initial processing parameters for thin-wall injection molding of post-consumer resin.
iv
This dissertation is dedicated to my family.
v
ACKNOWLEDGMENTS
I would like to express sincere gratitude to my adviser, Dr. Kurt W. Koelling, for
his priceless guidance, encouragement, and support throughout this work. I also would
like to thank Dr. Julie Ann Stuart and Dr. Blaine Lilly for their instruction,
encouragement and support. Special thanks go to Dr. L. James Lee for his considerable
advice and help. I wish to thank Dr. David Tomasko, Dr. Jose Castro, and Dr. Robert
Brodkey for their valuable suggestions and comments. I would like to thank Dr. Paula
Stevenson for her proofreading and many helps during the past five years. Thanks also
go to everyone who helped me in various ways, Paul Green, Leigh Evrard and Carl
Scott. I would like to thank previous and current colleagues in the polymer research
group.
In addition, Micro Metallics Corporation and Nova Chemical, Inc. donated postconsumer and virgin polymers, Eastman Kodak Company loaned two molds, Dow
Chemical donated polypropylene, 3M Company donated Dynamar 9613, and GenCorp
Research donated a blender. The authors thank Professor Terry Gustafson and research
assistants Tony Frost and Kristin Frost of the Chemistry Department at The Ohio State
University for measuring the infrared and Raman vibrational spectra. The author thanks
Dr. John Clay for the measurement of the molecular weight, and Michael Ferry, Tu Tran,
vi
Sadu Prabowo, Andy Divine and Eric Mosser for help in measuring some physical
properties.
Finally, I would like to thank my parents for their continuing support through the
years of my study and my wife, Xia Cao, for her understanding, support, and
encouragement.
vii
VITA
September 25, 1967…………………………..………Born - Cixi, Zhejiang, P. R. China
September 1985 - July 1989………………………….B.S. Chemical Engineering
Zhejiang University
Hangzhou, Zhejiang, P. R. China
September 1989 - March 1992……………………….M.S. Chemical Engineering
Zhejiang University
Hangzhou, Zhejiang, P. R. China
September 1998 – present….………………………...Graduate Research Associate
The Ohio State University
Columbus, OH
PUBLICATIONS
1. Guojun Xu and Kurt Koelling, "Flow Marks/Tiger striping during Thin-Wall
Injection Molding of Polypropylene", J. Injection Molding Technology (Submitted).
2. Jose L. Garcia, Kurt W. Koelling, Guojun Xu, and James W. Summers, “PVC
Degradation During Injection Molding: Experimental Evaluation”, Journal of Vinyl
& Additive Technology (In press).
3. Christiana Kuswanti, Guojun Xu, Jianhong Qiao, Julie Ann Stuart, Kurt Koelling,
and Blaine Lilly, "An Engineering Approach to Plastics Reuse", Journal of Industrial
Ecology, 6, 125-35, 2003.
4. Guojun Xu and Kurt Koelling, "Flow Marks during Injection Molding", ANTEC,
Nashville, TN, 566-70, 2003.
5. Guojun Xu, Jianhong Qiao, Christiana Kuswanti, Kurt Koelling, Julie Ann Stuart,
and Blaine Lilly, "Characterization of Virgin/Post-consumer Blended High Impact
viii
Polystyrene Resins for Injection Molding", J. of Applied Polymer Science, 84, 1-8,
2002.
6. Guojun Xu and Kurt Koelling, "Flow Marks during Injection Molding", ANTEC, San
Francisco, CA, 521-5, 2002.
7. Guojun Xu and Kurt Koelling, "Study of Flow Marks during Thin-Wall Injection
Molding", ANTEC, Dallas, TX, 604-7, 2001.
8. Guojun Xu, Jianhong Qiao, Christiana Kuswanti, Molly Simenz, Kurt Koelling, Julie
Ann Stuart, and Blaine Lilly, "Insight into Reuse of High Impact Polystyrene from
Post-Consumer Electronics Equipment Housing", IEEE International Symposium on
Electronics and the Environment, San Francisco, CA, 348-53, 2000.
9. G. J. Xu, Y. M. Li, Z. Z. Hou, L. F. Feng and K. Wang, "Gas-Liquid Dispersion,
Mixing and Heat Transfer in a Stirred Vessel", Can. J. of Chem. Eng., 75, 299-306,
1997.
10. Y. Li, G. Xu, M. Chen and K. Wang, "Slow Pelleting Coagulation of MBS Latex",
Chem. Eng. Res. & Des., 75, 81-6, 1997.
11. Xu Guojun, Lianfang Feng, Yunming Li and Wang Kai, 'Pressure Drop of Pseuoplastic Fluids in Static Mixers', Chinese J. of Chem. Eng. (English), 5(1), 93, 1997.
12. Y. M. Li, M. W. Chen, G. J. Xu, and K. Wang, "Continuous Slow Coagulation of
Polymer Latex in Series Agitated Vessels", 36th IUPAC International Symposium on
Macromolecules, IUPAC MACRO SEOUL'1996, Korea, 6-p01-01, 597, 1996.
13. Y. M. Li, G. J. Xu, M. W. Chen, S. H. Ou and K. Wang, "Slow Pelleting
Coagulation of Polymer Latex Emulsion", 36th IUPAC International Symposium on
Macromolecules, IUPAC MACRO SEOUL'1996, Korea, 6-p01-02, 598, 1996.
14. G. J. Xu, Y. M. Li and K. Wang, "Particle Growth Kinetics for Seed Coagulation of
Polymer Latex", 36th IUPAC International Symposium on Macromolecules, IUPAC
MACRO SEOUL'1996, Korea, 6-p01-03, 599, 1996.
15. Hou Zhizhong, Feng Lianfang, Li Yunming, Xu Guojun, Wang Kai and Pan Zuren,
"Power Consumption of Agitation in a Gas-liquid System" (Chinese), 7th National
Conference on Chemical Engineering, Beijing, China, B54, 424, 1994.
16. Hou zhizhong, Li Yunming, Feng Lianfang, Xu Guojun, Wang Kai and Pan Zuren,
"Study on Heat Transfer of Gas-liquid System in an Agitated Vessel" (Chinese), 7th
National Conference on Chemical Engineering, Beijing, China, B53, 420, 1994.
17. Hou Zhizhong, Wang Kai, Feng Lianfang, Li Yunming, Xu Guojun and Pan Zuren,
"Fluid/Wall Heat Transfer in an Agitated Gas-Liquid Reactor" (English),
International Workshop on the Advances in Chemical Engineering, Hangzhou,
China, 1994.
ix
18. Guojun Xu, Lianfang Feng and Kai Wang, "Pressure Drop and Friction Factor for
non-Newtonian Fluids in Static Mixers" (English), International Workshop on the
Advances in Chemical Engineering, Hangzhou, China, 1994.
19. Hou Zhizhong, Feng Lianfang, Li Yunming, Xu Guojun and Wang Kai, "Gas-liquid
Dispersion and Mixing Properties of Different Impellers in an Agitated Vessel",
China Synthetic Rubber Industry (Chinese), 18(3), 147-50, 1995.
20. Hou Zhizhong, Li Yunming, Feng Lianfang, Xu Guojun and Wang Kai, "Properties
of Gas-liquid Dispersion in a Baffle-gassed Multistage Agitated Vessel", China
Synthetic Rubber Industry (Chinese), 18(4), 218-20, 1995.
21. Guojun Xu, Zhangmao Wang and Gantang Chen, "Study of Axial Diffusion
Coefficients and Distinguish of Particulate/Aggregative Fluidization", Chemical
Reaction Engineering and Technology (Chinese), 10(3), 306-10, 1994.
22. Guojun Xu, Zhangmao Wang and Gantang Chen, "A Model of Fluid Flow and
Particle Circulation in a L/S Fluidized Bed", Chemical Reaction Engineering and
Technology (Chinese), 11(3), 277-83, 1995.
23. Guojun Xu, "Fluidized Polymerization Reactors", China Synthetic Rubber Industry
(Chinese), 18(1), 40-2, 1995.
24. Li Yunming, Xu Guojun, Ou Shuhui, Chen Miwen and Wang Kai, "Slow
Coagulation of Polymer Latex" (Chinese), Annual Conference on Polymers,
Guangzhou, 1179-80, 1995.
25. Zhizhong Hou, Lianfang Feng, Yunming Li, Guojun Xu and Kai Wang, "Heat
Transfer Properties in Aerated Agitated Reactor", China Synthetic Rubber Industry
(Chinese), 18(6), 338-40, 1995.
26. Yunming Li, Guojun Xu and Jingjing Xu, "A Study of Particle Growth in Seed
Coagulation of Polymer Latex" (Chinese), Annual Conference on Polymer,
Guangzhou, 1175-6, 1995.
27. Guojun Xu, Yunming Li and Jingjing Xu, "Methods of Seed Coagulation of Polymer
Latex" (Chinese), Annual Conference on Polymer, Guangzhou, 1177-8, 1995.
28. Zhangmao Wang and Xu Guojun, "A Study Expansion and Axial Diffusion in a
Liquid/Solid Spouted Fluidization Bed", Chemical Reaction Engineering and
Technology (Chinese), 12(2), 184-8, 1996.
29. Guojun Xu, Lianfang Feng, Yuming Li, and Kai Wang, "A Study of Pressure drop
for
Pseudo-plastics Fluids in Kenics Mixers", China Synthetic Rubber Industry
(Chinese), 19(2), 97-9, 1996.
x
30. Deming Mao, Lianfang Feng, Guojun Xu and Kai Wang, "Effect on Control Volume
and measured Points When the Beams Pass through Circular Media", Journal of
Experimental Mechanics (Chinese), 11(1), 13-7, 1996.
31. Deming Mao, Lianfang Feng, Guojun Xu and Kai Wang, "Experimental Study on
Agitator by LDA", Chem. Eng. J of Chinese University (Chinese), 10(3), 258-63,
1996.
32. Deming Mao, Lianfang Feng, Guojun Xu and Kai Wang, "Study of Spectral
Analyses and Scales of Turbulence in Rushton Turbine", Chem. Eng. J of Chinese
University (Chinese), 1996.
33. Yuming Li, Miwen Chen, Guojun Xu and Kai Wang, "Slow Pelleting Coagulation of
Polymer Latex Emulsion", Chinese Chemical Letter (English), 7(3), 297-8, 1996.
FIELDS OF STUDY
Major Field: Chemical Engineering
Minor Field: Polymer Processing
Rheology
Chemical Reaction Engineering
xi
TABLE OF CONTENTS
Page
Abstract…………………………………………………………………………………..ii
Dedication………………………………………………………………………………...v
Acknowledgments……………………………………………………………………….vi
Vita……………………………………………………………………………………..viii
List of Tables……………….……………………………………………………….…..xv
List of Figures……………………………………………..…………………………..xvii
Chapters
1. Introduction...……………………………………………………………….…………1
2. Literature review.……………………………………………………………….……12
2.1
2.2
2.3
Flow marks.…………………………………………………………………12
2.1.1
Alternate flow marks………………………...……………...…….13
2.1.2
Synchronous flow marks……………………………………...…..19
Experiment with micro-features and improvement of simulation accuracy
during thin-wall injection molding….………………………………..……..21
2.2.1
Thin-wall injection molding with micro-features…………..……..21
2.2.2
Cavity pressure and its prediction……………………………..…..34
Reuse of HIPS…………………………………………………..………...…37
3. Flow marks during thin-wall injection molding.……………………………………..45
3.1
Alternate dull and glossy flow marks….…………………………….……...45
3.1.1
Introduction………………………………………………………..45
xii
3.1.2
Experimental…………………………………………………….…47
3.1.3
Results and discussion…………………………………………….50
3.1.3.1 Rheological characterization…………………...……….50
3.1.3.2
Injection molding results……………………...…………51
3.1.3.3
Morphology and crystallinity…………………………....56
3.1.3.4
Extrusion…………………...……………………………57
3.1.3.5
Simulation………...……………………………………..57
3.1.3.6 Mechanism……………………...………………………59
3.1.4
3.2
Conclusion…………………...…...……………………………….64
Synchronous dull and glossy flow marks……………………………………65
3.2.1
Introduction………….……………………………………….…….65
3.2.2
Experimental………………………………………………………67
3.2.3
Results and discussion…………………………………….………69
3.2.3.1 Rheological characterization……………..……………...69
3.2.3.2
Injection molding results………………………………..69
3.2.3.3
Morphology and crystallinity…………………………....71
3.2.3.4
Extrusion…………………...……………………………72
3.2.3.5
Simulation……………...………………………………..72
3.2.3.6 Mechanism……………...……………………………….73
3.2.4
Conclusion………………..……………………………………….76
4. Experiment with micro-features and simulation accuracy improvement during thinwall injection molding………………………………………………...…….……..126
4.1
4.2
Thin-wall injection molding with micro-features………………..………...126
4.1.1
Introduction..…………...…………..…………………….……...126
4.1.2
Experimental……………...………………………….….………127
4.1.3
Experimental results….………………………………….………129
4.1.4
Simulation results….……………………………………………..132
4.1.5
Conclusions……………...………………...…..………………...134
Cavity pressure and its prediction during thin wall injection molding……135
4.2.1
Introduction..…………...…………..……………………………135
xiii
4.2.2
Simulation………………...………………………….……….…137
4.2.3
Results and discussion.…………………………………………..140
4.2.4
Conclusions……………...………………...…..………………...145
5. Characterization of virgin/post-consumer blended high impact polystyrene resins for
injection molding………………………………………………………...…………190
5.1
Introduction..…………………………………………………….…….…..190
5.2
Experimental.………………………………………………………………193
5.3
5.4
5.2.1
Characterization of materials…………………………………….193
5.2.2
Measurement of molecular weight………………………………193
5.2.3
Microscopy and spectroscopy……………………………………194
5.2.4
Processing parameters for ASTM specimens…………………....195
5.2.5
Physical properties of ASTM specimens………………………...196
5.2.6
Application……………………………………………………….197
Results and discussions…..……………………………………………..…198
5.3.1
Characterization of materials…………………………………….198
5.3.2
Molecular weight……...……………………………….………...199
5.3.3
Microscopy and spectroscopy……………………………………199
5.3.4
Processing parameters for ASTM specimens……………………200
5.3.5
Physical properties of ASTM specimens………………………...200
5.3.6
Application………………………………………………………203
Conclusions...……………………………………………………………...204
6. Conclusions and future work……...………………………………………………..225
6.1
Flow marks………………...………………………………….…….……..225
6.2
Experiment with micro-features and simulation accuracy improvement.…226
6.3
Reuse of HIPS……………………………………………….…………….230
References…….……………………………………………………………………….231
xiv
LIST OF TABLES
Table
Page
3.1
Relaxation time and zero viscosity at 200°C…..………………………………..78
3.2
Viscosity-molecular weight……………..………………………….…………...79
3.3
Average roughness of the dull and shiny regions……..…………………….…..80
3.4
Average roughness of the dull and shiny regions……..…………………….…..81
4.1
Orthogonal array of the simulation…………………………………………….147
4.2
Coefficients of Cross-WLF equation…………………………………………..148
4.3
Relative influence of each factor on peak cavity pressure at different injection
speeds at 230°C………………………………………………………………..149
4.4
Relative influence of each factor on peak cavity pressure at different injection
speeds at 250°C………………………………………………………………..150
4.5
Relative influence of each factor on peak cavity pressure at different melt
temperatures for HDPE at 0.5”/s………………………………………………151
4.6
Relative influence of each factor on maximum pressure drop at different injection
speeds at 230°C………………………………………………………………..152
4.7
Relative influence of each factor on maximum pressure drop at different injection
speeds at 250°C………………………………………………………………..153
4.8
Relative influence of each factor on maximum cavity pressure drop at different
melt temperatures for HDPE at 0.5”/s………………………………………….154
xv
5.1
Molecular weight and polydispersity…………………………………………..206
5.2
Weight percentage blends……………………………………………………..207
5.3
Mold design characteristics……………………………………………………208
5.4
Processing parameters from C-MOLD………………………………………...209
5.5
CMOLD parameters for film canister…………………………………………210
5.6
Tensile strength of film canisters……...…………………………………...…...211
xvi
LIST OF FIGURES
Figure
Page
1.1
Difference between thin-wall and conventional injection molding.…..……………….7
1.2
Typical molding problems (1)...……………………………...…..……………….8
1.3
Typical molding problems (2)...……………………………...…..……………….9
1.4
Typical molding problems (3)..……………………………...…..……………....10
1.5
Environmentally conscious engineering system perspective...…..……………...11
2.1
Alternate and synchronous dull and glossy flow marks.…………………………43
2.2
Thin-wall plate with microstructures………………….…………………………44
3.1
Alternate dull and glossy regions.....……………………………………...….….82
3.2
Comparison of viscosity vs. frequency at 200°C.…………………………..…...83
3.3
Comparison of complex viscosity of PP-C at 180, 200, and 220°C.……………84
3.4
Comparison of elastic and viscous modulus at 200°C…………………………..85
3.5
First normal stress difference vs. shear rate at 200°C……………………..….…86
3.6
The first normal stress difference of PP-C vs. shear rate at 180, 200, and
220°C……………………………………………………………………………87
3.7
Transient extensional viscosity at 130°C……………………………………..…88
3.8
Determination of relation time by one-mode Giesekus model………….…..…..89
xvii
3.9
Flow marks of PP-C at different injection speeds……………………….……...90
3.10
A typical example of the alternate dull and shiny flow marks…………….……91
3.11
Effect of melt temperature on the wavelength λ………………………….…….92
3.12
Effect of mold temperature on the wavelength λ……………………………….93
3.13
The effect of mold thickness on the wavelength λ……………………………..94
3.14
Effect of melt temperature on the width of the flow marks…………………….95
3.15
Effect of mold temperature on the width of the flow marks……………………96
3.16
The effect of mold thickness on the width of the flow marks…………………..97
3.17
The starting of the flow marks, Vcri vs. melt temperature………………………98
3.18
Effect of melt temperature on the transition velocity, Vtrans…………………….99
3.19
Flow mark zone of PP-C………………………………………………………100
3.20
Morphology of surfaces of dull and shiny regions………………………….…101
3.21
Gross melt fracture of the PP in extrusion………………………………….…102
3.22
The wall shear stress versus apparent shear rate in the extrusion………….….103
3.23
Wall shear stress vs. percentage filled in the thin spiral mold…………….…..104
3.24
The critical wall shear stress at the middle of the gate at different melt
temperatures…………………………………………………………………...105
3.25
The critical wall shear stress at the middle of the gate at different mold
temperatures…………………………………………………………………...106
3.26
The similarity between extrusion and injection molding processes…………...107
3.27
Oscillating flow generates alternate flow marks………………………….…...108
3.28
Frequency of the flow marks versus flow front velocity………………………109
3.29
Synchronous dull and glossy regions………………………………………….110
3.30
Comparison of viscosity vs. frequency at 180°C……………………………...111
3.31
Comparison of Elastic and viscous modulus at 180°C…………………….….112
xviii
3.32
First normal stress difference vs. shear rate at 180°C…………………………113
3.33
Extensional viscosity vs. time at 100°C……………………………………….114
3.34
Synchronous dull and shiny flow marks of HDPE2…………………………...115
3.35
Effect of melt temperature on wavelength…………………………………….116
3.36
Effect of mold temperature on wavelength……………………………………117
3.37
Effect of melt temperature on Vcri………………………………….…………118
3.38
Morphology of dull and shiny region of HDPE2……………………………...119
3.39
Flow curve of HDPE2 in extrusion……………………………………………120
3.40
Different extrudate irregularities at different wall shear stresses……………...121
3.41
Critical wall shear stress vs. percentage filled at different melt temperatures...122
3.42
Critical wall shear stress vs. percentage filled at different mold temperatures..123
3.43
Pulsating flow generates synchronous flow marks…………………………….124
3.44
Frequency of flow marks vs. Flow front velocity………………………………125
4.1
The long rectangular mold base with a disk-like insert………………………...155
4.2
The rectangular mold bases with a disk-like insert……………………………156
4.3
The disk-like mold insert which contains microchannels……………………..157
4.4
SEM picture of the a microchannel……………………………………………158
4.5
Dynamic viscosity of polypropylene…………………………………………..159
4.6
Dynamic viscosity of PMMA………………………………………………….160
4.7
SEM of a micro-channel……………………………………………………….161
4.8
Measured filling lengths in microchannels for PMMA in the long mold……..162
4.9
Measured filling lengths in microchannels for PP in the long mold…………..163
4.10
Measured filling lengths in microchannels for PMMA in the long mold……..164
4.11
Measured filling lengths in microchannels for PP in the long mold…………..165
xix
4.12
Measured filling lengths in microchannels for PP in the short mold…………..166
4.13
The cavity pressure profile in the long mold and the short mold……………...167
4.14
The filling length vs. Fourier number……………………….………………...168
4.15
The effect of packing stage on filling lengths..………………...……………...169
4.16
The effect of holding pressure on filling lengths..……………...……………...170
4.17
Comparison of the filling lengths between the simulation and experiment with
constant heat transfer coefficients. Main flow heat transfer coefficient=25000
W/m2.K………………………………………………………………………...171
4.18
Comparison of the filling lengths between the simulation and experiment with
constant heat transfer coefficients. Main flow heat transfer coefficient=2000
W/m2.K………………………………………………………………………...172
4.19
Comparison of the filling lengths between the simulation and experiment with
variable heat transfer coefficient………………………………………………173
4.20
Schematic of the mold with thickness of 1 mm……………………………….174
4.21
Heat capacity of HDPE and PS………………………………………………..175
4.22
Specific volume of HDPE……………………………………………………..176
4.23
Specific volume of PS…………………………………………………………177
4.24
Experimental and fit viscosity vs. shear rate/ frequency for PS……………….178
4.25
Experimental and fit viscosity vs. shear rate/ frequency for HDPE…………...179
4.26
Comparison of cavity pressure with/without the effect of pressure on specific
volume…………………………………………………………………………180
4.27
Comparison of cavity pressure with/without the effect of pressure on
viscosity………………………………………………………………………..181
4.28
Comparison of cavity pressure with different heat transfer coefficients……....182
4.29
Comparison of cavity pressure with constant Cp and temperature-dependent
Cp…………………………………………………………………………..….183
4.30
Comparison of cavity pressure with/without juncture loss………………….…184
xx
4.31
Pressure profiles right after the gate and at the end of the cavity at the injection
speed of 76.2 mm/s and the melt temperature of 230 and 250°C…………...…185
4.32
Pressure profiles right after the gate at the melt temperature of 230°C with
different injection speeds…………………………………………………...….186
4.33
Pressure profiles at the end of the cavity at the melt temperature of 230°C with
different injection speeds……………………………………………………....187
4.34
Comparison of experimental and predicted pressure drop at the injection speed of
12.7 mm/s…………………………………………………………………..….188
4.35
Comparison of experimental and predicted pressure drop at the injection speed of
508 mm/s………………………………………………………………………..189
5.1
Film canister………………………………………...…………………..……...212
5.2
Comparison of the viscosity curves for post-consumer HIPS and virgin HIPS at
220°C……………………….…………………………….……………………213
5.3
Viscosity of Huntsman PS 702 blends with different percentages of postconsumer resin at about 200°C………………………….……………………..214
5.4
Viscosity of Nova PS 3350 blends with different percentages of post-consumer
resin at about 200°C…………………………………………….……………..215
5.5
The images of different blends from ESEM (The length of the scales in the
figures are 2 µm)………………………………………………………..…...….216
5.6
Raman spectroscopy of injection-molded post-consumer and Huntsman PS
702………………………………………………………………………...…...217
5.7
Infrared vibrational spectra of injection-molded post-consumer and Huntsman PS
702………………………………………………………………………….….218
5.8
Average Ra for six blends of Huntsman PS 702……………………………….219
5.9
Average Wa for six blends of Huntsman PS 702……………………………....220
5.10
Tensile strength and tensile modulus vs. weight percentage of virgin resin...…221
5.11
Flexural strength and flexural modulus vs. weight percentage of virgin resin...222
5.12
Impact strength and tensile modulus vs. weight percentage of virgin resin…...223
5.13
Meshing model of the film canister……………………………………………224
xxi
CHAPTER 1
INTRODUCTION
Among the large number of polymer processing operations, injection molding
has found the widest application for making articles which could be put to direct use.
Because of the superior manufacturability and the high degree of freedom of the form of
plastics products, injection molding is one of the most widely used processes for
processing plastics. In injection molding process, the polymer melt flows through a
runner system and gates to fill the mold cavity. When the filling is completed, more
melt is packed into the mold to compensate for volume shrinkage. The cooling stage
follows until the melt solidifies. Finally the part is ejected from the mold. Thin-wall
injection molding (TWIM) is conventionally defined as molding parts that have a
nominal wall thickness of 1 mm or less and a surface area of at least 50 cm2 [Whetten
and Belcher, 1994; Fasset, 1995]. Thin wall is relative, however. It also can be named
“thin-wall” as the flow length/thickness ratio is above 100 or 150 [Mahishi, 1998;
Maloney and Poslinski, 1998].
TWIM has been paid more and more attention,
1
especially in computer, communication and consumer electronic (3C) industries, due to
economic and environmental concerns. The reason is that thin-wall molded parts could
be made lighter, more compact, less expensive, and quicker because of fast cooling
[Smialek and Simpson, 1998]. New environmental regulations require less plastic to be
used at the source or in the initial stage of manufacturing [Miller, 1995]. Thus, TWIM is
a viable option for reducing the weight and size of plastic components.
The difference between conventional injection molding and TWIM is shown in
Fig. 1.1. The solidified “skin” layers are about 0.25 mm regardless of part thickness
[Fasset, 1995]. It means that the flow channel is very narrow and thus flow resistance is
very high in TWIM. Reducing flow resistance can be reached by increasing the melt or
mold temperature, reducing melt viscosity (increasing melt index), increasing injection
pressure, or injection speed [Fasset, 1995; Belcher and Hoenig, 1991]. However, high
melt temperature may cause degradation and increases cooling time which are
unacceptable. A rise in melt index shows a decrease in physical properties [Belcher and
Hoenig, 1991].
Therefore, high injection speed is preferred, and extremely high
injection pressure, 200-250 MPa (30,000-40,000 psi), is required [Colangelo and
Tremblay 1997]. Due to the thin part, cooling is fast. Thus the combination of the fast
cooling and high melt velocity (short fill time) significantly reduces the cycle time. The
typical cycle time of TWIM is 6-20 seconds while the cycle time for conventional
injection molding is 40-60 seconds [Selden, 2000]. The shrinkage is also low because of
the reduced part thickness [Delbarre, et al., 1991]. TWIM is characterized as high flow
rate, high pressure, high shear rate, high viscous heating, fast cooling and fast shrinkage.
2
However, TWIM has some disadvantages. Due to the rapid cooling of the
polymer melt, the operating window becomes narrower as the part becomes thinner
[Bozzelli, et al., 1997; Coxe, et al., 2000]. Specialized material is also required to
balance the trade-off between processability and physical properties [Cha and Lai, 2000],
which means material should both flow easily (high melt index) and retain good physical
properties. TWIM also makes design and process control more complicated. It is a big
challenge to fill the mold with a high flow length/thickness ratio at a high speed under
high pressure. For example, an additional accumulator is needed to maintain high
pressure at a short fill time. However, the operation of the accumulator affects the
molding stability [Chen, et al., 2000]. More robust control systems are required to
control the molding precisely and with a short response time [Selden, 2000; Hatch, et al.,
2001]. High injection pressure also needs high clamp tonnage which increases the
capital investment of equipment.
Processing, material, tooling, and machine interact with each other and greatly
affect the end results. For TWIM, systematic investigation about machine performance,
mold design/manufacture requirement, molding characteristics, computer aided
engineering (CAE) simulation, part quality and part design criteria is required [Chen, et
al., 2000]. However, the study is lacking due to the difficulty of thin-wall molding
process.
Furthermore, the combination of viscoelastic materials, complex molding
geometry and cyclic processing conditions has generated some problems [Schmidt,
1998], such as flow marks, polymer degradation, high residual stress, sink marks and
warpage, under high-speed, high-pressure injection molding. So it is very important to
3
design, operate and control thin-wall molding optimally to guarantee part quality as well
as reduce cost.
In this study, some issues, such as surface flow marks, thin-wall
injection molding with micro-features, mold cavity pressure and its prediction, and reuse
of post-consumer resin, are investigated.
Part appearance is one important criterion for assessing part quality because it
can be quickly evaluated. There are many aesthetic indictors that include warpage,
surface finish or gloss level, flash, sink marks, short shot, color, burns, bubbles,
transparency, pecks, scratching, stress marks, splay, drag, streaks, etc. [Salamon, et al.,
1998]. Some typical surface problems are shown in Figs. 1.2-1.4 [C-Mold design guide,
1998]. Flow marks are one of these problems created during injection molding. They
exhibit different levels of gloss on the surface of molded parts. These surface defects are
related to the melt flow and are thus called flow marks. They are also referred to as tiger
stripes, striping, halos, slip-stick, haze patterns, webs, chatter marks, blush or rings
[Salamon, et al., 1998; Dharia, 1999]. These flow marks occur especially on automotive
exterior parts and are very difficult to mask with paint. The defects limit the use of
many polymers in unpainted applications. In this study, two types of flow marks,
alternate dull and glossy and synchronous dull and glossy flow marks, are studied.
In recent years, the fabrication of polymer-based micro-components for optical
and biomedical applications has been paid more and more attention. The polymer
material is favored because of its low cost, good bio-compatibility, high optical clarity,
and high impact strength compared with silicon or glass. Micro-injection molding has
the potential for economical mass-production. It usually combines various lithography
4
techniques and injection molding [Weber and Ehrfeld, 1999]. Two types of micro-parts
are available: micro-sized parts whose delivery system including the runner and sprue is
much larger than the parts themselves and regular-sized parts with micro-features.
Micro-injection molding (MIM) is the injection molding of plastic parts with structure
dimensions in the micron or sub-micron range. The replication of the micro-features is
an important issue and it depends greatly on the size, aspect ratio and covered area
[Weber and Ehrfeld, 1999]. This study focuses on the thin-wall injection molding with
micro-features by experiment and numerical simulation.
The filling lengths in
microchannels are simulated and compared with experimental results. Because the
predicted filling lengths in microchannels are very sensitive to the heat transfer
coefficients selected, it is necessary to study the effect of input property models on the
simulation outputs. We further study how the input properties affect the simulation
output in thin-wall injection molding. The output we choose is mold cavity pressure.
Injection mold cavity pressure is an important injection molding parameter.
It is
regarded as a good indicator of molded part quality and injection machine control
performance. Cavity pressure not only indicates the material condition in the mold but
also affects the microstructure and part quality. Computer Aided Engineering (CAE) is a
common practice nowadays to help design, process, optimize, and troubleshoot thin-wall
injection molding processes. However, almost all users prefer better accuracy of CAE
simulation because large discrepancy between simulation and experiment may occur.
The difference may result from simplifying some important physical, thermal or other
properties, such as the pressure-dependent viscosity, variable heat transfer coefficient,
5
and variable material properties. The goal of the study is to understand how pressuredependent viscosity, heat capacity, heat transfer coefficient, juncture pressure loss and
pvT-data affect pressure prediction, and the importance of each parameter.
Then
methods to improve the prediction accuracy will also be discussed.
As the increasing use of plastics, the plastics waste has become a main concern.
Environmentally conscious design and manufacturing is a strategic and competitive
practice.
The reduction of material consumption is a big challenge for industrial
ecology. The attention paid to polymer recycling has increased in the past decade.
However, the life cycle trade-offs between collection, disposal, use of recycled plastics,
recyclability, reduction of process wastes, energy consumption, yields, and product
performance are complex, as shown in Fig. 1.5 [Stuart, 1999]. Life cycle assessment
and life cycle production planning models are very useful tools to analyze these
tradeoffs. However, resin degradation characteristics and potential design details are
required in order to apply these tools. Plastics recycling is important because more
efficient re-use of materials will reduce the quantities of plastics sent to landfills as well
as reduce raw material extraction.
Waste prevention practices are increasingly
significant and are increasingly encouraged with the advent of take-back legislation
[Gamalski, 1996; Meffert and Kirchgeorg, 1997; Hubschman, et al., 1995]. In this
study, characterization and reuse of post-consumer resin (PCR) in a thin-wall application
is addressed.
6
Thin-Wall Part
(1 mm)
Conventional Part
(3 mm)
Flowing Core 0.5 mm
Flowing Core 2.5 mm
Solid Skin 0.25 mm
Solid Skin 0.25 mm
Fig. 1.1. Difference between thin-wall and conventional injection molding.
7
Black specks
black streaks
Brittleness
Burn marks
Delamination
Dimensional variation
Flash
Flow marks
Fig. 1.2. Typical molding problems (1) [C-Mold design guide, 1998].
8
Hesitation
Jetting
Ripples
Silver streaks
Fig. 1.3. Typical molding problems (2) [C-Mold design guide, 1998].
9
Fish eyes
Sink marks
Weld lines or Meld lines
Fig. 1.4. Typical molding problems (3) [C-Mold design guide, 1998].
10
Virgin
Materials
Raw Materials
Concurrent Product, Process
& System Design for
Assembly/Reuse/End-of-Use
Degradation Reusable Material
Model
Content Model
Manufacturing/Services
Energy
Rework
Distribution
Consumer
Repair
Recycling
Downcycling
Disposal
Fig. 1.5. Environmentally conscious engineering system perspective [Stuart, 1999].
11
CHAPTER 2
LITERATURE REVIEW
2.1 FLOW MARKS
The application of injection molding has greatly increased in recent years.
However, there is a conflict between the high quality of exterior appearance and short
cycle time. Injection molding sometimes creates several kinds of surface defects during
processing, differing levels of gloss on the surface of molded parts. The surface defects
are related to the melt flow and are thus called flow marks. They are also referred to as
tiger stripes, striping, halos, slip-stick, haze patterns, webs, chatter marks, blush or rings
[Salamon, et al., 1998; Dharia, 1999]. These matte areas occur on one or both sides of
parts. When they occur on both sides, those on one side of the parts are in phase or out
of phase with those on the other side of the parts. According to Yokoi [1994a], three
kinds of flow marks are classified according to the surface conditions of flow marks.
They are (1) micro-grooved zones like LP records, (2) synchronous dull and glossy
surfaces and (3) alternate dull and glossy surfaces. The kind of flow mark with microgrooved zones like LP records is also well known as wave-like flow marks. Flow marks
12
may occur on center-gated parts made with multi-phase polymer systems, including
rubber modified polymers, thermoplatic olefin (TPO), blends (HIPS, PC/ABS),
copolymer (ASA, ABS, EP), and semi-crystalline polymers (LDPE, HDPE, PP/Talc).
They may also occur on edge-gated parts [Salamon, et al., 1998].
Here we discuss two types of these surface defects: those associated with the
flow instability and those associated with the change of flow front velocity [Salamon, et
al., 1998]. One type of flow mark is characterized as alternate dull and glossy surfaces
where flow marks on one side are out of phase with those on the other side of the part, as
shown in Fig. 2.1(a). Another type of flow mark is characterized as repeated dull and
glossy regions where a dull/glossy zone on one side corresponds to a dull/glossy zone on
the other side, as shown in Fig. 2.1(b). These flow marks cause surface defects that
occur especially on automotive exterior parts. Flow marks can be very difficult to mask
with paint due to the change in porous structure of dull and shiny regions. The defects
also limit the use of many polymers in unpainted applications.
2.1.1 Alternate Flow Marks (AFM)
One type of flow mark is characterized as alternate dull and glossy surfaces
[Yokoi, 1994a]. Flow marks were observed as early as in 1961 and some work has been
done to explain and eliminate them [Yokoi, 1994b; Chang, 1996a; Chang, 1996b;
Hobbs, 1996; Heuzey, et al., 1997; Hamada and Tsunasawa, 1996; Dharia, 1999; Bulters
and Schepens, 2000; Grillet, et al., 2000; Charmeau, et al., 2000; Xu and Koelling, 2001;
Jayaraman, et al., 2002]. In the literature, the effect of operating variables, physical
13
properties of plastics, and mold geometry has been discussed. Operating variables
include injection speed, injection pressure, melt temperature, and mold temperature. The
physical properties cover different kinds of polymers, the rheology of polymer melt and
molecular weight distribution, while the mold geometry includes gates, mold thickness
and different molds. Moreover, several kinds of mechanisms have been proposed to
explain the generation of flow marks. However, little has truly been understood on why
flow marks occur and how to predict and eliminate them. Furthermore, the results in
literature sometimes conflict with one another.
Alternate flow marks were typically observed in LDPE and PP/talc and were
caused by a cyclic unsymmetrical flow front [Yokoi, 1994b]. There seemed to be a clear
correlation between the shear stress level on the cavity wall and the flow mark
generation region, and thus the flow marks were thought to occur due to the melt fracture
on the cavity surface. The flow marks may involve wall slip, though the author did not
state this. Chang used a slip mechanism to explain the surface defects [Chang, 1996a;
Chang, 1996b]. When ASA polymer melt flow meets a thickness change from gate to
cavity, slip can occur if the melt has low adhesion (friction) to the mold surface due to a
low die swell. The slip can initiate a melt flow instability. Thus, this kind of flow
instability causes flow marks with alternate dull and glossy regions. It was shown that
recoverable shear strain, shear stress and the coefficient of friction between the melt and
mold were key controlling factors for the generation of flow marks. It was also found
that the higher the ratio of step size, the more severe the degree of flow marks.
14
In a study of several blends of BPA polycarbonate and ABS resins, Hobbs found
that at higher injection rates, the flow marks were more continuous and pronounced
[Hobbs, 1996]. The study indicated that stick/slip flow at high wall shear stresses
created the flow marks and wall slip was worsened by lower friction coefficients. It was
found that wall slip first occurred on one face of the mold. When the melt front flow
chattered across the surface, high frequency ripples developed.
This kind of slip
generated a distortion in the velocity gradient across the flow channel and caused the
flow front to oscillate back and forth. The flow marks were formed by dragging the
partially solidified melt across the mold surface.
It was hypothesized that wall slip is associated with some kinds of flow marks.
However, Heuzey, et al. found no obvious relationship between the wall slip and flow
marks [Heuzey, et al., 1997]. Using linear polyethylene, they found that one of the
resins did not slip in capillary flow experiments. Furthermore, coating on a mold wall
did not affect the occurrence of flow marks. They concluded that wall slip does not
affect the occurrence of the flow marks. They believed that three main factors were
involved in the occurrence of alternate dull and glossy flow marks: the surface cohesive
strength of the semi-solidified polymer, the adhesion between the solid layer and the
mold, and the high shear stress in the melt near the wall. The generation of flow marks
was due to the filamentation and stretching of semi-solidified materials.
In the thin-wall injection molding experiment, flow marks with alternate dull and
glossy regions were studied using PC and ABS blend [Hamada and Tsunasawa, 1996].
It was found that when no flow marks occurred, PC and ABS flowed in steady, laminar
15
motion with a normal fountain flow and in layers due to its low viscosity. However,
when flow marks occurred, the PC and ABS flowed with oscillation. So, the center of
the flow moved in the direction of the mold thickness. This kind of abnormal fountain
flow happened because of the high viscosity of resin flow. Under this condition, high
shear stress is applied on the PC and ABS. The result was that the PC phase at the tip of
the flow front might be broken and then PC and ABS coexisted, causing cloudy (dull)
regions.
In a study of binary blends of polypropylene and ethylene co or ter-polymers
[Dharia, 1999], it was concluded that the increase in built-in stress between the skin and
core at the melt front increased surface defects. The study showed that the tendency was
the combined effect of rapid stress build-up and slow recovery. It was also found that
flow marks were caused by a melt flow instability and the inability of melt to recover
from the stress change at the flow front. More recently, Bulters and Schepens visualized
the mold filling process by a layered block of PP with contrasted colors. It was found
that the flow front was unstable and the black layer broke through at the surface. They
claimed that flow marks resulted from a flow front instability [Bulters and Schepens,
2000]. Furthermore, Grillet, et al. conducted a finite element simulation for a very strain
hardening fluid and a very strain softening fluid.
After the steady numerical
calculations, a linear stability analysis was performed and it was found that the most
unstable eigenvector was an oscillatory, swirling flow near the stagnation point at the
free surface [Grillet, et al., 2000]. Alternate flow marks of TPO blends were studied by
Jayaraman, et al. [2002]. The disperse phase morphology was analyzed in detail. It was
16
found that the rubber particles in the out of the flow mark region were highly stretched
and had a high aspect ratio, while the rubber particles in the flow mark region were less
stretched and had a low aspect ratio. It was concluded that the flow marks occurred in
the long spans of the unbalanced flow front.
The effect of mold geometry and processing variables was studied by Chang
[Chang, 1996b]. It was found that the mold thickness and mold surface temperature
were the controlling factors on flow marks. It was also found that a larger thickness
ratio caused more severe flow marks, and an increase in mold temperature decreased the
rank of defect severity. Though the increase of injection speed and pressure worsened
the flow marks, their effects were not as important as the above two factors. When
rubber levels decreased, surface appearance improved because of the combination of the
effect of recoverable shear strain and shear stress. As for the effect of carbon black
loading, surface defect severity increased with the increase of carbon black levels.
Chang concluded that the higher the melt elasticity, the better the surface appearance.
However, the surface appearance was improved by increasing the coefficient of friction
or decreasing the lubricant level.
Hobbs found that with the increase of the injection speed, the flow marks were
more continuous and pronounced [Hobbs, 1996]. The trend of the results is consistent
with Chang’s work [1996b]. High surface roughness values of compound lowered the
coefficient of sliding friction, increased stick/slip flow, and thus reduced gloss value.
In the injection molding for processing LLDPE and HDPE, flow marks with
alternate dull and glossy regions were formed [Heuzey, et al., 1997]. It was found that
17
the flow marks were affected by mold surface finish. In their experiment, injection rate
was the most important factor affecting the flow marks. The severity of flow marks
increased with the increase of the injection rate. It is consistent with Chang’s [1996a;
1996b) and Hobbs’ [1996] results. However, wall slip did not lead to in the generation
of flow marks. It was found that coating had no great effect on flow marks. However,
surface defects were amplified by adding silicone oil. It was also found that mold
thickness had a small effect on flow marks, but the observation was different from that
of Chang's work [Chang, 1996b].
In the thin-wall injection mold, flow marks were generated when processing a
PC/ABS blend [Hamada and Tsunasawa, 1996].
It was found that low cylinder
temperature, low mold cavity temperature and high injection speed were the factors
generating flow marks. The gate design was also found to be important.
Dharia found that the most important factor producing flow marks was lower
mold temperature [Dharia, 1999]. The second important factor was injection pressure,
while the third important factor was injection speed. It was found that the high injection
speed generated more pronounced flow marks. In all cases, even moderate backpressure
could reduce flow marks.
Although experimental evidences show that oscillating instability occurred in
mold filling [Chang, 1996a; Hamada and Tsunasawa, 1996; Bulters and Schepens,
2000], there is disagreement on why the instabilities occur and where it originates.
Furthermore, it is widely known that elastic instabilities occur upstream of a contraction,
such as a capillary die or slit die, in extrusion or spinning. [Piau, et al., 1988; White, et
18
al., 1987; Boger and Walters, 1993; Koelling and Prud’homme, 1991]. However, the
researchers studying the flow marks have not studied the entry instability and its
relationship to the flow marks, although Dharia already noticed the similarity between
extrusion and injection molding processes [Dharia, 1999].
In this study, we investigate the effect of operating parameters and different
polymer melts on the wavelength, width, and gloss variation of the flow marks. Then
several methods to reduce the flow marks are discussed. We study the correlation
between gross melt fracture in extrusion and alternate dull and glossy flow marks in
injection molding. Then, an entry viscoelastic flow instability mechanism is proposed to
explain the alternate flow marks.
2.1.2 Synchronous Flow Marks (AFM)
Although alternate dull and shiny flow marks and wavelike flow marks have
been studied in the literature [Tredoux and Satoh, 1999; Tredoux, et al., 2000; Yokoi, et
al., 1994a; Yoshii, et al., 1993; Yoshii, et al., 1996; Lee and Mills, 1994], little attention
has been given to synchronous flow marks [Yokoi, et al., 1994c; Salamon, et al., 1998].
The synchronous dull and glossy flow marks usually occur in high viscosity PP with a
narrow gate [Yokoi, et al., 1994c]. A glass-inserted mold was used to visualize the flow
front during the mold filling process, and homopolymer PP was used in their experiment.
It was observed that synchronous dull and glossy flow marks were generated, but no
flow marks were observed on the glass surface or polished cavity surface. It was found
that at high injection rates, many thin and narrow flow marks occurred [Yokoi, et al.,
19
1994c]. The gate shapes greatly affected the generation of flow marks and the flow
marks varied dramatically with the front flow velocity. At higher melt temperature, flow
marks became thinner. At the melt temperature of 240ºC, flow marks did not show up
where the variation of gate pressure and flow front velocity was small. They explained
that near the gate, the flow resistance was high causing the flow quantity to decrease.
The gate pressure was increased during the filling, while the melt velocity was decreased
at the flow front and the melt was cooled down. On the other hand, the gate was frozen
and the flow resistance was increased.
Therefore, the melt at the flow front was
accelerated with the release of the high gate pressure. At that moment, the resin near the
flow front underwent cooling, so the transcription precision decreased in the subsequent
fountain flow process. Then the flow marks were formed.
In the injection molding of HIPS in a rectangular mold with a center-gate, halos
similar to flow marks with synchronous dull and glossy regions were formed [Salamon,
et al., 1998]. It was found that the temperature gradient between any two zones was the
cause of the formation of the halos. It was also proposed that the temperature gradient
must decrease in the direction of the flow in order to form the halo and the halo could be
reduced by a design that minimizes the heat losses to reduce the temperature gradient. It
was also shown that the mold temperature was significant in controlling the halo. When
the mold temperature was high enough, the halo did not occur because the surface
stresses relaxed and recovered. However, the halo always appeared when the mold
temperature was set below the annealing temperature. With the increase of injection
rates, the halos became more prominent and the diameter of the halos became larger
20
because the thickness of the skin layer was reduced. It was also found that the part
surface was rougher in the halo region, and the valleys in the halo region were aligned
with the flow direction. They proposed that the stress was rapidly decreased for the
polymer melt from a colder zone to a hotter zone, causing rapid reduction of strain rate.
This reduction of strain rate therefore increased the size of the melt and the melt must
wrinkle or fold to respond to this increase because the melt was confined in the mold
cavity. The wrinkles or folds were aligned with the flow direction and quickly solidified
without relaxation when contacting the cold mold surface, causing flow marks to form.
This study considers the effect of operating parameters and mold surface coatings
on flow marks of different polymer melts. A possible correlation between gross melt
fracture in extrusion and synchronous dull and glossy flow marks in injection molding is
discussed. Finally, a possible mechanism is proposed.
2.2 EXPERIMENTS WITH MICRO-FEATURES AND IMPROVEMENT OF
SIMULATION ACCURACY DURING THIN-WALL INJECTION MOLDING
2.2.1 Thin-Wall Injection Molding with Micro-Features
In recent years, the fabrication of polymer-based micro-components for optical
and biomedical applications has been paid more and more attention. The polymer
material is favored because of its low cost, good bio-compatibility, high optical clarity,
and high impact strength compared with silicon or glass. Micro-injection molding has
the potential for economical mass-production. It usually combines various lithography
techniques and injection molding [Weber and Ehrfeld, 1999]. Two types of micro-parts
21
are available: micro-sized parts and regular-sized parts with micro-features. Microinjection molding (MIM) is the injection molding of plastic parts with structure
dimensions in the micron or sub-micron range. Micro-injection molding process meets
the requirement of cost-effective replication in large scale series. Different small or
micro components with the following specifications can be injection molded
[Hanemann, et al., 1997a]:
• Plate-shaped microparts with microstructures of any lateral form.
• Volume of the standard substrate base plate: 20×60×2 mm3 (width×length×height).
• Microstructure height up to 1.6 mm.
• Smallest wall thickness down to 30 µm.
• Smallest structure detail 0.2 µm.
• Aspect ratio up to 30:1.
• Suitable materials: PMMA, PC, PSU, POM, PA12, PEEK, etc.
Usually, micro structured mold inserts are made by special processes and then
attached to standard molds [Piotter, et al., 1997]. The critical dimensions which can be
produced by micro-injection molding in good shape are mainly determined by aspect
ratios.
Common microstructured products such as CDs and DVDs could not be
compared with LIGA microstructures with aspect ratios of ten to 600 [Piotter, 1997].
Modification of the molding machinery, the tool’s construction, and the molding
operation is demanded to injection molding of microstructures with high aspect ratios.
22
The main difference between thin-wall injection molding and micro-injection
molding is described in detail as follows:
a. Mold Technology
For thin-wall injection molding, high speeds and high pressures can make mold
plates flex. It may cause flash or thicker wall sections of molded parts. Thus thick and
strong molds are required in thin-wall injection molding to resist high pressure. TWIM
also requires relatively large and/or multi gates for easier mold filling. More ejection
pins are needed because parts are tightly packed. Larger ejection pins are used to avoid
part distortion. Sometimes vacuum evacuation is recommended to minimize weld lines
and possible burning of compressed gas [Fasset, 1995]. However, usually venting along
the parting line combining the venting of ejectors and core pins can solve this problem.
In injection molding of microstructures, micro structured mold inserts are made
and then attached to standard molds. The mold cavity can be prepared by LIGA process
or more traditional processes such as micro-turning, micro-sparking and laser-erosion
[Piotter, et al., 1997]. LIGA process is a relatively new process to produce molds or
cavities. Typically, micro mold inserts have high aspect ratios, especially from LIGA
process. Parallel plane walls and lacking of injector slope make demolding difficult.
However, multi-stepped master structures can be produced by inclined x-ray exposure,
two-stepped resist structures, or the combination of several microstructuring techniques
[Piotter, et al., 1997]. These techniques generate pretty smooth surface (roughness is
smaller than 10 nm). Molds must meet high demand, such as accuracy requirement.
23
Because conventional venting through parting planes or gaps is impossible for
microstructures due to the “blind holes” in microstructures [Hanemann, et al., 1997a],
venting is a problem. Compressed hot air may burn the polymer, so compressed air must
be evacuated by a vacuum pump. The mold inserts should be carried out certain number
of shots in practice. To avoid damage, it is wise to reduce stress on the mold insert. The
variothermal heating is a good choice in this point because high temperature lowers
viscosity and makes the mold inserts easy to be filled. Reducing injection pressure or
holding pressure is a choice. Wear is another problem. It is reported that wear did not
occur after 1000 shots for LIGA mood inserts made from nickel or nickel-cobalt [Piotter,
et al., 1997].
b. Machine Technology
For thin-wall injection molding, high injection speed, 500 mm/s, is preferred and
extremely high injection pressure, 200-250 MPa, is required [Colangelo and Tremblay,
1997]. The purpose is to reduce flow resistance caused by narrow flow channels. High
clamping force is also required because of high pressure. High clamp tonnage means
high capital investment of equipment. Due to the thin part, cooling is fast. Thus the
combination of the fast cooling and high melt velocity significantly reduces the cycle
time. Precise control is required to get good surface finishing. TWIM also makes
design and process control more complicated. It is a big challenge to fill the mold with a
high flow length/thickness ratio at a high speed under high pressure. For example, an
accumulator is needed to maintain a high pressure at a short fill time. More robust
24
control system is required to control the molding precisely within a short response time
[Selden, 2000].
Development of micro-injection technology started in early 1980’s.
No
appropriate injection molding machine was available at that time and people had to
modify the commercial hydraulic driven units with a low clamping force. To mold
microstructures, people usually use a small screw in a conventional screw-injection
molding machine. However, the screw is easy to be broken under shear. To reduce the
shot size suitable for microstructures, people adopt properly sized runner systems or
directly inject melt into cavities using a hot runner nozzle without runner systems
[Rogalla and Michaeli, 1997].
Brand new injection molding machine for
microstructures was under development in middle 1990’s. The machine developed at
FZK can inject very small amount of resin, for example 0.025g, with a stable process
[Piotter, et al., 2001]. The machine for micro-injection molding includes venting and
variothermal heating systems. In contrast to thin-wall injection, high injection pressure
and speed are not essential. Of course, injection pressure and speed as well as other
parameters influence the part quality and dimension stability, which is also true for thinwall injection molding.
Incomplete filling is a main concern in micro-injection molding. People use a
variety of reaction injection methods to reduce viscosity. The common method is using
photoinduced polymerization of MMA/PMMA based resins. The molding can be
conducted at ambient temperature using a machine with a small sized powerful UV light
25
source. The polymerization time of 2.5 minutes could be obtained [Hanemann, et al.,
1997a]. Thermally initiated RIM is another technique. A relatively simply and reliable
mold filling and good accuracy could be obtained because of the low viscosity of the cast
resin. Resins based on acrylates, methacrylates, amides and silicones are thermally
curable. However, this technique needs elevated temperature to start polymerization.
The process is relatively slow and also needs mixing and metering units.
c. Material
For thin-wall injection molding, the material should flow easily, have enough
impact strength and high stiffness and resist polymer degradation due to shear heating.
However, good flowing ability (high melt index) usually means low physical properties.
So, specialized material is required to balance the trade-off between processability and
physical properties. Some suitable materials especially for thin-wall injection have been
developed. Appropriate materials for micro-injection molding must have low viscosity
but satisfactory mechanical properties. Common materials used are PMMA, PC, PSU,
POM, PA12, PEEK, etc.
d. Operating
In thin-wall injection molding, the pressure and velocity are very high. TWIM
prefers low viscosity and it mainly relies on high shear rate instead of high temperature.
The mold temperature usually is low in order to accelerate heat transfer and reduce
cooling time. Due to the rapid cooling of polymer melt, the operating window is
narrower as the part becomes thinner.
26
Common injection molding parameters such as relatively low mold temperature
and injection pressure will cause incomplete filling of mold inserts. In order to fill the
mold inserts completely, the temperature on the surface of mold inserts is usually heated
up to melt temperature. This is so-called variothermal heating. Usually the temperature
is above glass transition point for semi-crystalline polymers and near melting point for
crystalline polymers to reduce flow resistance. The mold is completely filled just before
the ejection because conventional venting method is impossible for microstructures.
However, it will inevitably increase the cycle time if using a variothermal process. The
shortest cycle time reported is 70 s with aspect ratio of only 2.5 and microstructures with
high aspect ratios needs more than 6 minutes [Piotter, et al., 1997], which is much longer
than thin wall injection molding.
It should be noted that for most microstructures with low aspect ratios (<2),
usually a constant temperature is used but the temperature is higher than that in
conventional injection molding.
e. Simulation
The modeling of micro-injection molding is different from conventional or thinwall injection molding process.
Several models have been developed during last
decades to simulate the filling of conventional injection molding. Most injection molded
parts are complex, the filling process is non-isothermal, and polymer fluids demonstrate
non-Newtonian behavior. So, it is very difficult to simulate the filling process without
simplification. The pioneering work focused on pressure and temperature prediction of
27
simple geometries. Usually, a generalized Hele-Shaw flow model is used to simplify the
governing equations for non-isothermal, non-Newtonian melt flows. In most cases, the
simplification successfully predicts the modability (pressure and velocity fields, air
entrapment, temperature distribution and stress concentration regions) [Hetu, et al.,
1998].
The Hele-Shaw approximation neglects flow in the gapwise direction [Garcia , et
al., 1991]. So, the velocity in the thickness direction w=0.
Continuity equation:
∇⋅u = 0
Momentum equation:
∇P + ∇ ⋅ σ (u ) = 0
σ i (η ) = 2µγ& (η ) = η (∇u + (∇u ) T )
The Hele-Shaw approximation can be written as
∇ ⋅ S∇P = 0 i.e.
H
where S = ∫ (
0
z2
η
∂
∂P
∂
∂P
(S ) + (S ) = 0
∂x ∂x
∂y ∂y
)dz
Because the heat conduction in flow direction can be neglected, energy equation can
expressed as:
ρC p (
∂T
∂T
∂T
∂
∂T
+u
+ v ) = (k ( )) + Φ
∂t
∂x
∂y
∂z
∂z
where Φ is viscous heating.
28
Boundary conditions:
Injection gates:
Q=Q(t) or P=P(t)
T=Tmelt
Moving flow fronts:
P=0
T=Tcore
Mold wall:
u⋅n = 0
T=Tmold or q=h(Tw-T)
It should be noted that the no-slip does not hold anymore after the Hele-Shaw
approximation.
However, these models are limited in the scope of the information that they can
generate. Furthermore, the Hele-Shaw approximation can not accurately predict the
fluid behavior at flow front and the flow behavior near or at solid walls, the phenomenon
occurring at the merging of two or more streams (weld lines), and the kinematics in
gates, ribs, or sudden thickness change, the areas where shear and extensional
deformations contribute significantly to the stress field [Gao, et al., 1998]. A threedimensional simulation could provide complementary and more detailed information.
However, because of its intensive computation nature, 3D simulation started only several
years ago [Han and Gupta, 1999]. The difficulties met in simulating 3-D filling are
[Gao, et al., 1998]:
29
• The computational domain is usually a 3D volume having a complex shape.
• The free surface is subject to large deformations and multiple interfaces may
come in contact with each other.
• The prediction of the flow boundary layers requires no-slip boundary condition.
The equations of continuity, momentum and energy can be expressed as [Chang and
Yang, 2001]:
∂ρ
+ ∇ ⋅ ρu = 0
∂t
∂
( ρ u ) + ∇ ⋅ ( ρ u u − σ ) = −∇P + ρ g
∂t
σ = η (∇u + (∇u ) T )
ρC p (
∂T
+ u ⋅ ∇T ) = ∇(k∇T ) + ηγ& 2
∂t
The boundary conditions [Gao, et al., 1998]:
u = u 0 ; T = Tmelt at Γinlet
σ (u ) ⋅ n − P n = t on Γtractions
u = 0; T = Tmold or q=h(Tw-T) on Γwall
The tracking of the evolution of melt front is usually modeled by pseudo-concentration
method:
∂f
+ ∇ ⋅ (u f ) = 0
∂t
30
where f=0 is defined air phase, and f=1 as melt phase. The inertia term and body force
term in momentum equation and viscous heating in energy equation can be neglected
sometimes [Gao, et al., 1998].
For thin-wall injection molding, the Hele-Shaw approximation is usually used
and it generally provides good results. However, the results are not perfect and error is
large in some cases, as discussed above. Furthermore, due to the characteristic of thinwall injection molding, the main reason of unsatisfied results is due to the inaccurate
description of polymer physical properties in the unstable process. Because of extremely
high pressure, the effect of pressure on compressibility and viscosity should be
considered. Because the typical filling time is 0.2 s in thin-wall injection molding, the
temperature changes dramatically.
The isothermal condition combining with high
pressure make it very difficulty to describe the heat conductivity, heat capacity,
especially heat transfer coefficient. Study showed that neglecting the effect of pressure
on viscosity may cause large error in predicting cavity pressure. The heat conductivity
and heat capacity used are often measured at constant temperature and low pressure. So,
the main effort to improve the prediction accuracy focuses on the improvement of the
property description, which will be discussed in detail in Section 2.2.2.
Simulation of micro-injection molding is a new area and very little work has
1
been done. For flat and thin parts, so-called standard injection molding parts, 2 D
2
codes usually provide good results. However, difficulty occurs when simulating the
filling of microstructures with high aspect ratios [Piotter, et al., 1997; Hanemann, et al.,
31
1997b; Yu, et al., 2001]. Although the simplification by assuming thin and flat parts
makes calculation easy and fast, the dimensional character of microstructures is not thin
and flat anymore. The examples are micro parts like micro gearwheels, micro sensors,
etc.
It is expected that the simplification does not hold anymore and proper 3D
simulation is necessary. For the parts with microstructures, such as LabCD, they show
thin-wall plates with microstructures, as shown in Fig. 2.2. Hele-Shaw approximation
gives the average information in gapwise direction in the large thin plate. Obviously,
local information of T, P and v at inlet of the micro-channel is crucial for the simulation
of the flow in the micro-channel. So, it will cause big discrepancy in simulating the
microstructures. Furthermore, viscosity and surface tension are even more important for
microstructures. The surface roughness may also play a significant role in
microstructures. Moreover, the material data, especially rheology data for macroscopic
application should be re-examed when applied to micro scale. Previous study showed
1
that 2 D simulation such as C-MOLD is not sufficient to describe all molding effects
2
anymore for extremely small structures of microparts [Hanemann, et al., 1997b].
Modifications
to
most
conventional
programs
such
as
MOLDFLOW
and
CADMOOULD-SD or new 3-D transient codes are required in order to simulate the
filling of micro-injection molding [Hanemann, et al., 1997b]. For the thin part with
microstructures such as LabCD, the modification can be as follow: Using 2D codes to
simulate the flow in the large domain while using 3D to simulate the flow in the
microstructures [Hanemann, et al., 1997b].
32
In this study of the thin-wall molding of base plate with microchannels, the
velocity variation in the width direction y is negligible, a 2D x-z plane simulation is
used. The momentum equations, the continuity equation and the energy equation are
written as follows at a quasi-steady state [Yu, et al., 2004a]:
∇ ⋅ ( ρv ) = 0
∇ ⋅ ( ρvu ) − ∇ ⋅ (η∇u ) = −
∂p
∂x
∇ ⋅ ( ρvv) − ∇ ⋅ (η∇v) = −
∂p
∂z
∂
( ρC p T ) + ∇ ⋅ ( ρC p vT ) = ∇ ⋅ (k∇T ) + H
∂t
where
H
⎡ ⎛ ∂u ⎞
= η ⎢2⎜ ⎟
⎢⎣ ⎝ ∂x ⎠
2
+
⎛ ∂v ⎞
2⎜ ⎟
⎝ ∂z ⎠
2
⎛ ∂u
+⎜
⎝ ∂z
∂v ⎞
+ ⎟
∂x ⎠
2
⎤
⎥
⎥
⎦
In this study, thin-wall injection molding with micro-features was studied
experimentally and numerically. The filling lengths in microchannels are simulated and
compared with experimental results.
Because the predicted degree of filling in
microchannels are very sensitive to the heat transfer coefficients selected, it is important
to study the effect of selection of property models on simulation outputs. We then
further study how the input properties generally affect the output in thin-wall simulation.
The output we choose is mold cavity pressure.
33
2.2.2 Cavity Pressure and its Prediction
Injection mold cavity pressure is one of the most important parameters in thinwall injection molding. It is regarded as a good indicator of molded part quality and
injection machine control performance [Angstadt, 2001; Dubay, 2001]. It not only
indicates the material condition in the mold but also affects the microstructure and part
quality [Macfarlane and Dubay, 2000; Gao, et al., 1996; Gao, et al., 1996]. Cavity
pressure can affect part weight, dimensions, cosmetics, gloss, warpage, shrinkage, etc.
[Bozzelli and Cardinal, 1996]. It is therefore very useful to study the effect of injection
operating variables and material properties on cavity pressure (gradient). Usually, low
cavity pressure is preferred because low pressure demands low injection capacity that
reduces equipment cost, reduces shear orientation, and produces low shear stress which
is essential to avoid quality problems such as warpage and low mechanical properties.
Low stress is even more important in stereolithography [Dell’Arciprete, et al., 1999;
Palmer and Colton, 2000] or micro-injection molding [Yu, et al., 2001] where mold
wear and durability are main concerns.
Today it is common to use computer aided engineering (CAE) programs to
successfully design a part.
CAE can be used to troubleshoot and solve problems
concerning filling time, injection pressure, gate location and dimension, warpage,
coolant efficiency, etc. [Kalnin and Zluhan, 1999]. The application of CAE has the
potential to reduce overall production cost and improve part quality. Using CAE to
34
analyze part quality has given encouraging results and it is possible to design a good
mold without any tool tryouts [Kansal, 2000].
However, almost all users would prefer better accuracy of CAE simulation
[Ainoya and Amono, 2001]. During thin-wall injection molding (TWIM), the error of
the prediction of cavity pressure from CAE simulation can vary from 50% to more than
100%, and the error increases as the parts become thinner [Chen, et al., 2000]. The
discrepancy may result from neglecting some important factors during simulation. For
example, the effect of pressure on viscosity is important because of very high pressure
which occurs in TWIM [Chen, et al., 2000; Amano and Ainoya, 2000; Fasset, 1995;
Mahishi, 1998]. However, accurate pressure-dependent data are rare and not available
commercially. The actual testing is time consuming, expensive, and test equipment is
not commonly available [Ainoya and Amono, 2001]. The heat transfer coefficient
between the part and mold wall changes with time and operating variables. It affects the
cooling time and melt pressure. However, it is usually a constant in commercial CAE
packages. For example, both C-MOLD and MoldFlow set a default value of 25,000
W/m2⋅K, which result in higher predicted cavity pressure. Chen, et al. [2000] noticed
that material properties might be the reason for the prediction discrepancy. Ainoya and
Amono [2001] found that pvT-data affected fill time and cavity pressure. They also
found that the heat transfer coefficient and pressure-dependent viscosity had a great
effect on pressure prediction. Cavity pressure drop was extremely overpredicted when
the effect of pressure on viscosity and juncture loss were not considered. Slightly lower
filling pressure was predicted when the tabulated heat capacity was used instead of
35
constant heat capacity. However, the thermal conductivity had little influence on filling
pressure. Sherbelis and Friedl found that neglecting the effect of pressure on viscosity
led to overprediction of cavity pressure, while neglecting the juncture loss led to
underprediction of nozzle pressure [Sherbelis and Friedl, 1996]. Sridhar and Narh
[1999] found that the heat capacity and thermal conductivity had almost no effect on
cavity pressure, but they could affect cooling time and part shrinkage and warpage.
Another cause for the discrepancy between simulation and experiment is the lack of a
high quality database for the polymer, such as heat conductivity and pvT data [Chen, et
al., 2000]. For example, viscosity and thermal properties are usually measured under
equilibrium conditions, and they greatly affect simulation accuracy when these
properties, such as pvT data, are used in non-equilibrium injection molding process
[Chen, et al., 2000]. Furthermore, the difference may result from the difference between
the actual molding conditions and set conditions.
For example, the actual melt
temperature and injection velocity may be greatly different from the set parameters
[Ainoya and Amono, 2001]. Thus the set parameters do not reflect the actual melt
conditions and using these parameters for simulation results in the difference between
the simulation results and experimental results.
Some work has been conducted to study the effect of material properties on
pressure. However, a systematic study of the effect of these parameters is rare. In this
study, the effect of pressure-dependent viscosity, heat capacity, heat transfer coefficient,
juncture pressure loss and pvT-data on cavity pressure and pressure drop prediction will
be considered, and the importance of each parameter will be evaluated. Then the
36
simulation results and measured data will be compared. Finally the method to improve
the prediction accuracy will also be discussed. The study aims to help in understanding
which material property is important and needs rigorous testing, in order to improve
simulation accuracy and reduce time and cost for expensive property testing.
2.3 REUSE of HIPS
As the demand for plastics is increasing, the disposal of plastics is also
increasing. World thermoplastic consumption was over 100 million kilograms in 2000
[Society of the Plastics Industry, 2001]. However, only approximately 5.4% of postconsumer plastics was recovered in the US [U.S. Environmental Protection Agency,
2002]. Plastics recycling is important because more efficient re-use of materials will
reduce the quantities of plastics sent to landfills as well as reduce raw material
extraction. Waste prevention practices are increasingly significant and are increasingly
encouraged with the advent of “take-back” legislation [Gamalski, 1996; Meffert and
Kirchgeorg, 1997; Hubschman, et al., 1995]. It is accepted that direct use of postconsumer polymer is the most efficient and reliable way to treat plastic waste [Kartalis,
et al., 1999]. However, how to characterize the post-consumer resin and how to increase
the percentage of the post-consumer resin are two of the problems in recycling plastic.
High impact polystyrene (HIPS) occupies a large market share in computer,
business machines, and other electronics [Arola and Legarth, 1999].
Furthermore,
monitor housings and printers are two of the largest applications. However, less than
37
1% is recovered from the total 19% market share of HIPS [Dillon and Aqua, 2000].
Therefore, it is important to evaluate and develop viable options for discarded polymer
products. However, the analysis of life cycle trade-offs between use of recycled plastics,
recyclability, reduction of process wastes, energy consumption, yields, and product
performance are complex [Allenby and Laudise, 1995; Stuart, et al., 1999; Szekely and
Laudise, 1995]. To date, many companies process either 100% virgin material or virgin
material with small percentages of regrind. Sources of post-industrial regrind may be
internal or from another industrial processor(s).
Companies embracing product
stewardship are struggling to develop viable approaches to process and recycle returned
products economically.
Post-consumer polymers may be contaminated by other
materials [Langerak, 1997]; post-consumer products may contain polymer blends as well
as additives such as reinforcements, paint, or flame retardants [Dillon, 1999]. Thus,
post-consumer plastics introduce additional raw material uncertainties into the
manufacturing process. In addition, incompatible polymer blends may be present in a
product, requiring expensive disassembly procedures or less valuable mixtures. As a
result, many plastics recyclers currently select between options such as incineration or
downcycling, the formation of lower grade polymer materials. Another complication is
that returned polymers have been exposed to various thermal and mechanical conditions
and degradation could happen.
One important challenge in post consumer resin recycling is the contamination
from other materials. If the contaminants are not removed, then the mixed materials may
be “down-cycled” for use in simpler applications than their original products.
38
Contaminants may be metal, stickers, or other polymers. The level of contamination in
post-consumer resins depends on the product design and the separation techniques used.
After hazardous materials such as batteries are removed manually, disassembly or
automatic size reduction (shredding) follows.
Separation techniques may include
manual labor, magnets, air separation, or float sink approaches [Hendrix, et al., 1996].
Langerak [1997] compared there different separation methods for television housings:
(1) complete manual disassembly; (2) manual removal of front and back casings,
shredding, magnetic ferrous metal removal, and float-sink separation of nonferrous
metals and plastics; and (3) complete shredding, magnetic ferrous metal removal, and
float-sink separation of nonferrous metals and plastics. Langerak concluded that option
2 was the most cost effective materials recovery method. Because many variations of
plastics have similar densities, plastics identification based on density may not be
sufficient.
So, contamination is still a concern because option 2 relies on density
separation.
Furthermore, identification marks usually appear at the most general level, such
as low-density polyethylene, and do not include information such as the manufacturer
product code or manufacturer.
Even recyclers with close relationships with
manufacturers and suppliers and sophisticated information links have faced challenges to
identify materials from the model number [Grenchus, et al., 1998]. Moreover, the
source of plastics collected is correlated to the age and diversity of the materials. For
example, the plastics from municipal solid waste collection will be older and contains
39
more diverse assortment than the plastics from post-industrial regrind. Thus, further
characterization of the actual post-consumer resins is required through testing.
Another big challenge is the material degradation. During polymer processing,
such as injection molding, materials undergo severe thermal histories and mechanical
loadings (shear and extensional flows) that produce molecular degradation. Molecular
degradation of plastics usually decreases the polymer chain length and leads to a
decrease in melt viscosity and mechanical properties of the final product. The degree of
degradation varies significantly depending on the type and amount of polymer and
additives used in each commercial resin. Blending polymers for recycling has been
studied in the context of improving the properties of PCR [Liu and Bertilsson, 1999].
Several researchers have studied property degradation during thermoplastic
recycling processes. Ries and Menges [1988] studied the degradation of polypropylene
and found a decrease in impact strength due to a decrease in molecular weight. They
believed that the melt index could be useful in predicting the molecular weight, which
may allow off-line monitoring of impact strength degradation. Zahavich, et al. [1992]
showed that viscosity and swell ratio are the best indicators for degradation of an HDPE
resin. This is not surprising, since swell ratio is a strong function of the high molecular
weight fraction. Pagel [1989] showed that reground ABS exhibits very stable physical
properties over successive regrind generations, but the resins became yellow.
Dzeskiewicz, et al. [1993] studied the decrease in mechanical and rheological properties
of glass-filled nylon with successive generations, but showed that more than 50%
regrind could be blended with virgin resin to exceed specifications.
40
The degradation of polymer chains due to mechanical stresses (shear and
extensional flows) has been an object of scientific interest for at least 50 years, starting
with the Frenkel’s work [Frenkel, 1944]. Using a bead-spring model, Frenkel predicted
that the polymer chains would align with the flow, that the stress would be maximum in
the middle of the chain, and that as a result the middle of the chain would be the site of
fracture. Scientists have observed mid chain fracture for a variety of polymers under
various flow conditions. The flow birefringence experiment on polystyrene showed that
the degradation products formed a narrow distribution around half the molecular weight
of the initial polymer molecules [Odell and Keller, 1986]. Nguyen and Kausch [1986]
studied the degradation of polystyrene in a different flow device, and found that the
polymer degraded to a broad molecular weight distribution. These studies point to the
importance of understanding how thermal history and mechanical stresses impact
polymer degradation.
Studies have been conducted on determining the number of cycles a polymer can
be molded [Shriver, et al., 1994; Bernardo, et al., 1996].
Bernardo, et al. [1996]
developed a model to predict the properties of virgin/recycled polymer mixes based on
the number of previous processing cycles. This information is useful in determining the
materials recycling threshold for polymer components. In isolated cases where housings
are returned to the original manufacturer, the number of cycles may be tracked
[Timmons, 1998]. However, in most cases, it is not viable to track the number of
processing cycles.
41
To use PCR, it is important to decide the processing parameters quickly in
injection molding application. However, the challenge is how to characterize the PCR in
order to injection mold it.
Suppliers of virgin materials provide ranges of typical
property values for tensile strength, tensile modulus, impact, mold shrinkage, and other
characteristics [GE Plastics, 1992].
Some companies seek used polymers with
certification of their mechanical properties [Jones, 1996]. Furthermore, manufacturers
often use mold filling simulation software with virgin resin databases to reduce the time
to determine initial processing parameters. A major gap is that current databases do not
contain entries for used resins. Although Narh, et al. [1999] investigated the viscosity
and injection molding processing parameters for post-consumer ABS, PC, and nylon 5.5,
with mold-filling simulation and design software, they did not specify how they obtain
their inputs for the PCR in a mold-filling simulation. Without material characteristic
data of the PCR, molders cannot easily determine whether a PCR may be a candidate for
use alone or in blends with virgin resins depending on the material characteristics and
the complexity of the application. Designers are hesitant to include post-consumer
recycled material content. Further complicating the inclusion of recycled materials is the
uncertainty of material content, contaminants, and degradation [Eriksson, et al., 1998].
In this study, we describe our progress in evaluating the viability of reusing postconsumer and virgin polymer blends of high impact polystyrene from electronics
equipment housings. The study also introduces a new approach to determine initial
processing parameters for injection molding of post-consumer resin.
42
Dull region
λ
Dull regions are on the phase
on the top and the bottom
a. Alternate dull and glossy regions.
Dull region
λ
Dull regions are out of phase on
the top and the bottom
b. Synchronous dull and glossy regions.
Fig. 2.1. Alternate and synchronous dull and glossy flow marks.
43
Microchannels
Main flow direction
Fig. 2.2. Thin-Wall plat with microstructures.
44
CHAPTER 3
FLOW MARKS DURING THIN-WALL INJECTION MOLDING
3.1 ALTERNATE DULL AND GLOSSY FLOW MARKS
3.1.1 Introduction
Several kinds of surface defects may occur during injection molding. One type
of surface defect is characterized as alternate dull and glossy surfaces in which flow
marks on one side of the part are out of phase with those on the other side [Yokoi,
1994a], as shown in Fig. 3.1. This is often referred to as tiger striping. This surface
defect occurs especially on automotive exterior parts. Some work has been done to
explain and eliminate flow marks [Yokoi, 1994b; Chang, 1996a; Chang, 1996b; Hobbs,
1996; Heuzey, et al., 1997; Hamada and Tsunasawa, 1996; Dharia, 1999; Bulters and
Schepens, 2000; Grillet, et al., 2000; Charmeau, et al., 2000; Xu and Koelling, 2001;
Jayaraman, 2002]. Several mechanisms have been proposed to explain the generation of
flow marks. However, little has been truly understood on why flow marks occur and
how to predict and eliminate them. A slip mechanism was proposed by Chang [Chang,
1996a; Chang, 1996b]: When the melt has low adhesion to the mold surface, slip can
occur and initiate a melt flow instability. Thus, this kind of flow instability can cause
45
flow marks with alternate dull and glossy regions. Hobbs believed that stick/slip flow at
high wall shear stresses caused flow marks [Hobbs, 1996]. Conversely, Heuzey, et al.
[1997] found that there was no obvious relationship between the wall slip and flow
marks. Furthermore, coating on a mold wall did not affect the occurrence of flow marks.
They believed that the generation of flow marks was due to the filamentation and
stretching of semi-solidified materials. Hamada and Tsunasawa [1996] found that in
cases where flow marks occurred, the PC and ABS flow oscillated, while in cases where
no flow marks occurred, the PC and ABS flowed in steady laminar motion with a normal
fountain flow. In a study of binary blends of polypropylene and ethylene co or terpolymers, Dharia [1999] proposed that the flow marks were generated by melt flow
instability and the inability of melt to recover from the stress changes at the flow front.
More recently, Bulters and Schepens claimed that flow marks resulted from a flow front
instability [Bulters and Schepens, 2000]. Furthermore, Grillet, et al. conducted a linear
stability analysis and found that the most unstable eigenvector was an oscillatory,
swirling flow near the stagnation point at the free surface [Grillet, et al., 2000].
The effect of operating variables, physical properties of plastics, and mold
geometry has been discussed. Although experimental evidences show that oscillating
instabilities occurred in mold filling [Chang, 1996a; Hamada and Tsunasawa, 1996;
Bulters and Schepens, 2000], there is disagreement on why the instability occurs and
where it originates. In this section, we study the effect of operating parameters and
different polymer melts on the wavelength, width, and gloss variation of the flow marks.
Then several methods to reduce the flow marks are discussed. Furthermore, it is widely
46
known that elastic instability occurs upstream of a contraction, such as a capillary die or
slit die, in extrusion or spinning [Piau, et al., 1988; White, et al., 1987; Boger and
Walters, 1993; Koelling and Prud’homme, 1991]. However, the researchers studying the
flow marks have not studied the entry instability and its relationship to the flow marks,
although Dharia already noticed the similarity between extrusion and injection molding
processes [Dharia, 1999]. We study the correlation between gross melt fracture in
extrusion and alternate dull and glossy flow marks in injection molding, then propose an
entry viscoelastic flow instability mechanism to explain the alternate flow marks.
3.1.2 Experimental
Molding experiments were conducted on a Sumitomo SG M-HP 180-ton
injection molding machine. The materials used were four types of polypropylenes,
namely PP-A, PP-B, PP-C and PP-D. Two spiral molds were employed with different
thicknesses (1.58 and 3.17 mm). The width of the mold channel was 1". The total flow
length was 16". The melt temperature was 204.4, 223.9 and 232.2°C. The mold
temperature for most experiments was set at a constant value of 29.4°C. The mold
temperature was changed to 79.4, 51.7, and later to 18.3°C. Two rectangular molds
were also employed with a thickness of 5.08 and 1mm. The length and width of the
mold channels was 150 and 51 mm, respectively. The edge gates used were 2.54 and 0.5
mm in thickness for the thick and thin mold, respectively. The melt temperature was
190, 225 and 260°C. The mold temperature ranged from 22 to 85°C. The effect of
47
holding pressure and injection pressure was studied at melt temperature 190°C, mold
temperature 22°C, and injection speed 0.4 m/s where the flow marks were pronounced.
For the parts that exhibited tiger striping marks, the wavelength λ was measured.
The wavelength λ was the distance from one shiny region to another on one side. We
also measured stripe width, which was the width of one shiny region.
The rheological properties were measured by a Rheometrics RMS 800. The
complex viscosity, storage and loss modulus, and first normal stress difference of each
polypropylene sample were measured at 180, 200, and 220°C, respectively.
The
extensional viscosity was measured at 130°C by a tensile tester, Instron 8511, based on
the standard ASTM test. The samples were standard tensile bars with 13 mm in narrowsection width, 57 mm in total length, and 3.2 mm in thickness. To obtain a constant
strain rate, one needs to program the Instron machine to follow the exponential-type
increase of sample length. The viscosity-molecular weight was measured based on
ASTM D445-97.
To check the slip effect, Dynamar 9613 (a 3M product), a fluorocarbon
elastomer, was used as a coating agent. It is a slip promoting product. Its dilute acetone
solution, ca. 1%, was coated on the hot mold surfaces to allow evaporation of the
solvent. We also studied the disappearance of the flow marks by directly adding a small
amount of Dynamar, 0.2%, into the PP-C pellets. The resin was well mixed before tests.
Samples were collected after 100 shots to stablize.
A Differential Scanning Calorimeter (DSC) from TA Instruments, DSC 2920,
was used to measure the crystallinity of dull and shiny regions. The sample was scanned
48
from 30 to 200°C at the rate of 10°C/min. A Scanning Electron Microscope (SEM),
Philips XL 30, was employed to observe the morphology of dull and shiny regions. An
optical profilometer, Wyko NT330, was used to measure the roughness of the dull and
shiny regions.
A two-stage single-screw extruder (Rheomex 252p) from Haake was applied to
exam the melt fracture phenomenon that usually shows up with PP. The screw had a
diameter of 3/4 inch and a length to diameter ratio (L/D) of 25. The diameter of the
capillary die used was 1.2 mm and its length was 12.
Because it is very difficult to estimate the wall shear stress during mold filling,
C-MOLD 2000 was used to simulate filling our spiral molds. C-MOLD is a set of
integrated computer aided engineering (CAE) simulations for plastics molding
processes, including injection mold filling, post-filling and cooling, part shrinkage and
warpage. CAE provides an easy-to-use data visualizer for viewing mesh information
and analysis results. First, the geometry was built, and then a mesh with 672 elements
was set up for C-MOLD simulation. In the simulation, all four types of polypropylenes
were adopted in both thin and thick molds. Moldflow Plastics Insight (MPI) 3.0, a
software integrating C-MOLD 2000 and Moldflow Plastics Insight 2.0, was used to
simulate filling our rectangular molds to estimate the wall shear stress at the gate. The
geometry and the mesh with 754 elements built in C-MOLD was imported and then the
simulation was run on MPI 3.0.
In the simulation, the values of the processing
parameters, such as shot size, injection pressure, holding pressure, holding time, mold
49
temperature and cooling time, were the same as those in the real injection molding
processes.
3.1.3 Results and Discussion
3.1.3.1 Rheological Characterization
The complex viscosity of PP-A, PP-B, PP-C, and PP-D was measured at 180,
200 and 220oC, respectively. Fig. 3.2 shows the complex viscosity of four polymer
melts at 200oC. It was found that the complex viscosity decreased with an increase in
frequency, and PP-C had the largest viscosity at the same frequency. Fig. 3.3 shows the
complex viscosity of PP-C at different temperatures. Fig. 3.4 shows the storage modulus
and loss modulus of different PPs at 200oC. It was found that the storage modulus and
loss modulus of PP-C were the largest. Also we can see that the storage modulus of PPC was very close to its loss modulus, as compared to other PPs. Fig. 3.5 shows the first
normal stress difference N1 versus shear rate at 200oC. PP-C had the largest N1 at the
same shear rate. Fig. 3.6 shows the first normal stress difference N1 versus shear rate at
180, 200 and 220oC, respectively. Fig. 3.7 shows the transient extensional viscosity at
130oC when the strain rate was 0.01 s-1.
It was found that PP-C had the largest
extensional viscosity at the same moment. It was also found that in the range of tested
shear rate and time, the ratio of N1/extensional stress was PP-C > PP-D > PP-A or PP-B
at the same conditions.
To determine relaxation time, we shifted all dynamic viscosity η' and elastic
material function 2η"/ω data to the master curve at 200oC using time-temperature
50
superposition and fit the data with the 1-mode Giesekus model [Bird, et al., 1987], as
follows:
τ = τS + τ P
τ P + λ1τ P1 − α
.
λ1
{τ P .τ P } = − ηP γ
ηP
.
τS = − ηS γ
An example is shown in Fig. 4.8. The relaxation time determined from the
model fit for different materials is shown in Table 3.1. We found that PP-C had the
•
longest relaxation time, and therefore the largest Deborah number (De=λ γ ) at the same
shear rate. Thus PP-C is the easiest material to develop a viscoelastic flow instability.
The viscosity-molecular weight of all four polymers measured is listed in Table 3.2.
3.1.3.2 Injection Molding Results
Experimental trials were conducted in the spiral molds at first. It was found that
PP-A and PP-D did not generate flow marks. However, flow marks usually occurred for
PP-C and PP-B under a certain range of processing conditions. The flow marks are
generally out of phase between the top and the bottom of the part. However, the shiny
region on one surface is not exactly in the center of two neighboring shiny regions on the
opposite surface. The flow marks that occurred were characterized as alternate dull and
shiny regions. Flow marks of PP-C occurred when the flow front velocity was as low as
0.01 m/s for the thick mold and 0.1 m/s for the thin mold. When the injection speed was
51
very low, the flow marks occurred at the end of the flow length. They did not occur
immediately after the distance of about one wavelength from the gate. With the increase
of the injection speed, flow marks became more pronounced. When the injection speed
was higher, flow marks occurred immediately after the polymer melt entered the mold
cavity. Also, the flow marks were very pronounced. When the injection speed was
increased further, flow marks became dimmer. When the injection speed was above a
critical value the flow marks disappeared. The width and discernible level of shiny
regions changed along the flow length. Usually, flow marks at the end of the flow length
were pronounced. Even for the same shiny region, the width changed in the width
direction. Usually, the shape of the shiny region also changed along the flow length, and
in some cases irregular shapes appeared. Fig. 3.9 shows a typical set of samples of flow
marks for PP-C.
For PP-B, the flow marks are similar to those of PP-C. However, because of the
filler, the color of the molded parts was yellowish and the flow marks were less
pronounced, making it very difficult to distinguish the neighboring dull and shiny
regions. Although we can notice the flow marks, it is very difficult to measure the
wavelength and width of the flow marks except in a narrow range of flow front velocity
at which the flow marks are apparent. It was observed that the wavelength and width
increased with the increase of flow front velocity. Above a critical flow front velocity,
the flow marks disappeared. Although the wavelength is close to the wavelength of PPC at the same conditions, the width of flow marks of PP-B is narrower compared to that
of PP-C.
52
In the thick rectangular mold, the alternate dull and shiny flow marks of PP-C
only occurred above a certain injection speed. At first the flow marks gradually became
more pronounced as the injection speed was increased; however, with the further
increase of injection speeds, the flow marks became less visible and finally disappeared.
This phenomenon is somewhat different from other researchers’ observations that the
flow marks became more severe as the injection speed increased [Chang, 1996b; Hobbs,
1996; Heuzey, et al., 1997]. A typical example of alternate dull and glossy flow marks is
shown in Fig. 3.10. In the thin rectangular mold, alternate dull and shiny flow marks of
PP-C occurred once the mold was filled.
The wavelength and stripe width of the flow marks of PP-C were measured. The
wavelength is defined as the distance from one shiny region to another on one side,
while the stripe width is the width of a single shiny region. Fig. 3.11 shows the effect of
flow front velocity on the wavelength in the thin mold. It was found that for the thin
mold the wavelength increased with an increase in flow front velocity, and then
remained relatively constant. Moreover, the wavelength was almost the same at the
same flow front velocity. However, the higher the melt temperature, the longer the final
wavelength. Fig. 3.12 shows that the mold temperature has little effect at low flow front
velocities; however, at higher flow front velocities, the higher the mold temperature, the
longer the wavelength.
Fig. 3.13 shows that the thicker mold exhibits a longer
wavelength. Thus a longer wavelength can be contributed to a higher melt temperature,
a higher mold temperature, and a thick mold. Fig. 3.14 shows the effect of melt
temperature on the width of the shiny stripes in the thin mold. It was found that the
53
width of the shiny stripes increased with an increase in the flow front velocity. At a low
flow front velocity, the melt temperature had little effect on the width of the shiny
stripes; however, at a higher flow front velocity, the higher the melt temperature, the
wider the shiny stripes. Fig. 3.15 shows that the mold temperature does not have much
effect when the flow front velocity is small, yet the width of the shiny stripes increases
as the mold temperature is increased at a high flow front velocity. The trend of the
change of the width is very similar to the trend of the change of the wavelength. Fig.
3.16 illustrates that the width of the shiny stripes increases with the increase of mold
thickness. Compared to previous work [Xu and Koelling, 2001], the effect of mold
temperature and melt temperature was clearly observed in the rectangular molds.
For the gloss variation of the flow marks of PP-C in the thin rectangular mold, it
was found that increasing either melt or mold temperature made the flow marks less
visible. The observed effect of mold temperature and thickness is in agreement with
Chang’s work [Chang, 1996a; Chang, 1996b]. The effect of melt temperature in our
experiment agrees with Hamada and Tsunasawa’s result [Hamada and Tsunasawa,
1996]. It was found for the first time that the flow marks were less visible as the holding
pressure was increased.
However, injection pressure had almost no effect on the
visibility of the flow marks, which was different from other researchers’ observations
[Chang, 1996b; Dharia, 1999].
Furthermore, the effect of the molecular weight of PP-C was studied. Adding
20% PP-D into PP-C greatly alleviated the flow marks, and the flow marks were scarcely
54
visible compared to pure PP-C at the same operating conditions. However, adding 20%
PP-A had little effect.
From the above discussion, the flow marks could be reduced by one or more of
the following factors: high injection speed, high melt or mold temperature, mold surface
coatings, and/or changing molecular weight or its distribution.
The flow marks occurred only above a certain flow front velocity in the thick
mold, Vcri. It was further found that the mold temperature almost had no effect on Vcri.
Vcri scarcely changed at different mold temperatures. However, Vcri increased as the
melt temperature was increased, as shown in Fig. 3.17.
The effect of the coating on the surfaces of the mold or gate was also studied. It
was found that a coating on the mold surfaces could not prevent the occurrence of the
flow marks, although it could alleviate the flow marks and make them less pronounced.
One interesting phenomenon is that coating on the mold surfaces did not change the Vcri,
implying that slip is not the cause of the alternate flow marks. The reason is that coating
on the mold surface reduces the critical shear stress where the slip occurs, thus
decreasing the Vcri where the slip is triggered.
Another interesting phenomenon observed was that the flow marks disappeared
at high injection speeds, which has not been reported previously. We define it as the
transition velocity, above which the flow marks disappear.
Fig. 3.18 shows the
transition flow front velocity vs. melt temperature. It was found that the transition
velocity increased as the melt temperature was increased.
55
However, the mold
temperature almost had no effect on the Vtrans. The zone of the flow marks in which the
flow marks may occur in operation is shown in Fig. 3.19.
It was found through our experiment that mold surface coatings increased the
Vtran. It was further found that adding 0.2% Dynamar into PP-C also increased the Vtrans.
It is well known that a slippery surface or adding a small amount of fluorelastomer into
the polymer reduces the wall shear stress at which slip occurs [Yang, et al., 1998;
Kazatchkov, et al., 1995].
This implies that the slip is not the cause for the
disappearance of the flow marks at high injection speeds. The reason is that the slippery
surface or the addition of Dynamar decreases the wall shear stress where slip occurs,
thus decreasing the Vtrans at the same operating variables. Therefore, slip does not cause
the flow marks to disappear.
Their disappearance may be due to the higher melt
temperature induced by high flow front velocity, and thus greater shear heating.
3.1.3.3 Morphology and Crystallinity
The Differential Scanning Calorimeter (DSC) experiment showed that no
difference in crystallinity was observed between the dull and shiny regions. The sample
thickness was about 100 micrometers. From the scanning electron micrograph (SEM), it
was found that polymer molecules were highly oriented in the shiny region, but the
polymer molecules were only slightly oriented in the dull region, as shown in Fig. 3.20.
This is in agreement with other researchers’ results, except that either high orientation or
no orientation was observed for shiny regions [Charmeau, et al., 2000]. The measured
average roughness by optical profilometer was smaller in shiny regions than in dull
56
regions, as shown in Table 3.3. The reported average roughness is the average value of 5
randomly selected positions.
3.1.3.4 Extrusion
The PP was extruded at the die temperature 170°C. It was found that when the
wall shear stress was low the extrudate was smooth, but gross melt fracture occurred at
higher wall shear stresses. The extrudate irregularity was wavy, as shown in Fig. 3.21.
The wall shear stress was estimated by
∆P
without the Bagley correction, where ∆P
4L / D
is the pressure drop in the die, L is the die length, and D is the diameter of the die. The
apparent shear rate was calculated by
32Q
, where Q is volumetric flow rate [Macosko,
πD 3
1994]. The experiment showed that the critical wall shear stress for the onset of the
gross melt fracture was 0.13 MPa. This is in agreement with other researchers' results
[Kazatchkov, et al., 1995]. The flow curve is shown in Fig. 3.22.
3.1.3.5 Simulation
It is very difficult to obtain wall shear stress and temperature profiles during
filling the spiral molds. By the C-MOLD simulation, the wall shear stress at the center
of flow front was obtained. Fig. 3.23 shows the wall shear stress of different polymer
melts vs. filling percentage at the injection speed of 0.1 inch/s in the thick mold. It was
found that generally, the wall shear stress of PP-C > PP-D > PP-B > PP-A at the same
57
filling percentage. At the same operating conditions with an injection speed of 0.1
inch/s, melt temperature of 204.4°C, and mold temperature of 29.4°C, the wall shear
stress of PP-C was about 0.13 MPa, while PP-B was only about 0.05 MPa. 0.05 MPa is
much smaller than 0.13 MPa above which macroscopic slip usually occurs for PP
[Kazatchkov, et al., 1995; Hatzikiriakos, 1991]. However, our experiment showed that
PP-B usually had flow marks. PP-D showed no flow marks, although its wall shear
stress was larger than that of PP-B. It was concluded that slip is unlikely the reason for
the generation of the flow marks in our case. Furthermore, slip could not explain why
the flow marks disappear at even higher injection speeds.
MPI 3.0 was used to obtain the wall shear stress during filling of the rectangular
mold. The critical wall shear stresses of PP-C at the middle of the gate were obtained at
Vcri where the flow marks began to form. The processing parameters and the Vcri used
had been determined from the injection molding experiment. Fig. 3.24 shows the critical
wall shear stress at the middle of the gate at different melt temperatures. It was found
that the wall shear stresses were in a narrow range. That means the flow marks start to
form at a wall shear stress of around 0.24 MPa at the gate at different melt temperatures.
Fig. 3.25 shows the critical wall shear stress at the middle of the gate vs. the filling
percentage at different mold temperatures. The figure shows that the wall shear stress
generally was very close at different mold temperatures. From the simulation, it was
found that flow marks of PP-C started at the same critical wall shear stress almost
independent of melt or mold temperature.
58
3.1.3.6 Mechanism
In injection molding, the process that polymer melts experience is similar to that
in extrusion. The general picture of these processes is that the polymer melt meets a
contraction and experiences high shear at the die or gate, then the polymer melt leaves
the die or gate and the polymer molecular chains relax, as shown in the following Fig.
3.26. Therefore, the melt fracture in extrusion processes and the flow marks in injection
molding are related, although a difference in the movement of polymer melts exists
between extrusion and injection. In extrusion processes, the shear rate at the die is on
the order of 1000 1/s [Schramm, 1994]. After the melt leaves the die, the melt swells
and moves like a plug flow with a free boundary. The shear rate is zero and the shear
stress at the surface is zero if we neglect the small extension near the surface. For
injection molding processes, the shear rate in the gate is higher than in the die. After the
melt leaves the gate, the melt moves in the mold, but the swell of the melt is restricted by
the mold wall because of the rigid boundary. Also the wall shear rate and wall shear
stress are still large, although they are much smaller than in the gate. The shear rate is
on the order of 10,000 1/s in the nozzle.
In extrusion processes, when the shear stress is low, the surface of extrudates is
smooth. However, flow instabilities occur when the stresses are sufficiently high. The
extrusion stability is associated with the appearance of distortion on the extrudate
surface, sometimes accompanied by oscillatory flow. Usually, melt fracture is a general
term used to describe different irregularities and instabilities that generate distortions and
non-smooth surfaces. Denn proposed a set of instabilities of LLDPE [Denn, 1990;
59
Denn, 2001]. When the shear stress reaches a critical value, typically about 0.1 MPa, the
surface becomes rough and wavy, which is commonly called sharkskin or surface melt
fracture. This type of irregularity with wavelengths is much smaller than the capillary
radius, and is about 1/10-1/5 of the overall specimen diameter [Loenov and Prokunin,
1994]. At a higher stress, the alternate smooth and sharkskin occurs. It is known as slipstick, or spurt flow. At a still higher stress, a transition region occurs where the surface
is relatively smooth with long-wavelength distortion. At a much higher stress, gross or
wavy distortion occurs. The wavelength is about the specimen diameter [Loenov and
Prokunin, 1994]. This set of phenomena is common for linear polymer melt, such as
HDPE, LLDPE, and PBD. However, most branched polymers do not show sharkskin or
slip-stick regions [Denn, 2001].
They only exhibit gross distortion.
Sometimes
extrudates exhibit smooth surfaces again when the stress is much higher than the stress
where gross melt fracture occurs. It is commonly known as superextrusion and was well
reviewed by Leonov, et al. [Loenov and Prokunin, 1994]. It is believed to result from
the uniform slip along the die.
The gross melt fracture has been studied for more than 50 years. However,
controversy still exists about the melt fracture phenomenon [Piau and Agassant, 1996;
Piau, et al., 1990a]. There are two common mechanisms in the literature to explain the
melt fracture [Piau and Agassant, 1996]. Some researchers believe that slip at the die
wall is the origin of the melt fracture. However, Den Otter clearly showed that wall slip
at the die could not explain the melt fracture [Den Otter, 1970]. Most researchers agree
that an entry instability causes gross melt fracture [Piau and Agassant, 1996; Larson,
60
1992]. The instability is also affected by various properties, such as polymer structure,
geometry of die entry, melt temperature, and die temperature [Piau and Agassant, 1996].
For viscoelastic fluids, a Newtonian fluid-like corner vortex may occur at a low
flow rate. The streamlines are the same as those of Newtonian creeping flow with a
small corner vortex, named "Moffatt eddy". The corner vortex zone is a dead zone that
does not interact with the fluid outside. The formation of vortices may be due to the
increasing extensional viscosity with the deformation rate or also due to the shearthinning effect [Den Otter, 1970; Cogswell, 1972]. Two different pathways are possible
for the development and growth of vortices as the flow rate is increased [Rothstein and
McKinley, 1999; Rothstein and McKinley, 2001]. For some viscoelastic fluids, the
corner vortex grows in strength as the flow rate is increased [Yesilata, et al., 1990]. At a
very high flow rate, the corner vortex grows upstream, fluctuates, and makes the flow
field entirely unstable. For some other viscoelastic fluids, two types of vortices coexist.
One is the corner vortex, and the other is the lip vortex [Yesilata, et al., 1999]. As the
flow rate is increased, corner vortex and lip vortex recirculating areas expand; then lip
vortex gradually develops and invades the corner vortex, and finally generates a single
area of recirculation [Piau and Agassant, 1996]. At a still higher flow rate, the flow
becomes unstable, and the vortex pulsates or rotates, causing a global change of flow
structure [Rothstein and McKinley, 2001; Boger, et al., 1986]. It is yet not clear whether
lip vortices occur for a given viscoelastic fluid. However, researchers found that its
occurrence depends on fluids and contraction ratio, i.e. the ratio of diameter upstream to
the diameter of the contraction [White, et al., 1987; Rothstein and McKinley, 1999].
61
It was found that the development of upstream instabilities governed the
appearance of the extrudates and the helix pitch. Above a critical stress, the flow
instability occurs independent of downstream flow conditions [Piau, et al., 1990b]. The
melt fracture occurs when the vortex is unstable. The amplitude and frequency of
pulsation increases with the pressure [Piau and Agassant, 1996]. Usually the frequency
of surface distortion and the vortex pulsation is identical.
As a result, we expect that vortices may form and an instability may happen at
the entry in injection molding when the flow rate is high enough, since extrusion
processes and injection molding processes are similar although differences exist between
extrusion and injection molding. The oscillating entry instability can propagate and
affect the downstream flow. Thus, the symmetrical oscillating flow may occur in the
mold, and the different thermal and shearing history of the melt causes alternate flow
marks. In fact, the oscillating flow has been found in other researchers’ experiments
[Hamada and Tsunasawa, 1996; Bulters and Schepens, 2000; Yokoi, 1994b]. Our
experiment showed that PP-C exhibited gross melt fracture at a high flow rate, i.e., the
entry instability occurred before a contraction, although the surface is smooth at a low
flow rate. It is therefore not surprising that the PP-C exhibits alternate dull and glossy
flow marks. As discussed above, slip is not the reason for the generation of the flow
marks. Some researchers [Xu and Koelling, 2002; Heuzey, 1997] already excluded slip
as the possible reason. It is also well known that PP behaves like a branched polymer.
This means that its molecular chains are not highly entangled and so the slip-stick
phenomenon does not occur.
62
One interesting question is why so many polymers exhibit gross melt fracture, yet
fewer polymers are reported as apparently showing flow marks. The reason may be due
to the different geometry of contraction used in extrusion and injection mold processes.
It was found that the symmetrical contraction generates vortex more easily than a nonsymmetrical contraction, such as planar die [White, et al, 1987]. Many researchers used
capillary die in extrusion, while most gates in injection are usually not symmetrical.
Viscoelastic melts therefore show vortices and thus gross melt fracture in extrusion, but
are less likely to exhibit vortices in injection molding (and thus flow marks).
This mechanism could explain our experimental results of flow marks. At a low
injection speed, the flow is stable and no flow marks occur. At a high injection speed
that reaches a critical wall shear stress, an entry flow instability occurs, resulting in
symmetrical oscillating flow that generates alternate flow marks, as shown in Fig. 3.27.
As the injection speed increases, the wall shear stress increases. The melt becomes more
severely sheared and the flow marks become more pronounced. However, with a further
increase of the injection speed, shear heating becomes more important and the melt
temperature is increased. This may make molecular chains easier to relax and thus less
sheared, so the flow marks are less visible.
Finally, the flow marks disappear.
Increasing the melt temperature or mold temperature decreases the wall shear stress and
thus makes the flow marks less visible. The effect of holding pressure is complicated. It
may be explained as follows: Although increasing the holding pressure increases the
wall shear stress, the high viscous heating increases melt temperature and thus makes the
flow marks less visible. The effect of injection pressure was very unusual, although it
was probably overshadowed by the effect of holding pressure in our case. So no clear
63
effect of injection pressure on the visibility of the flow marks was observed in our
experiment. People found that the frequency and amplitude of the vortex increased with
the increase of flow rate [Den Otter, 1970]. So the wavelength and width of the flow
marks increased as the flow front velocity was increased. Furthermore, the frequency
increased with the increase of flow front velocity, as shown in Fig. 3.28. The trend of
frequency is similar to that of gross melt fracture in extrusion [Den Otter, 1970].
Increasing the melt or mold temperature may increase both the wavelength and the width
of the flow marks. This may be explained as follows: The increase of melt or mold
temperature decreases wall shear stress, causing a more stable entry flow.
The
molecules relax and move more easily in the mold cavity. As for the effect of the mold
thickness, the oscillating flow has more space to move before it hits the mold wall and
bounces back in the thick mold although the gate wall shear stress is smaller. So the
wavelength and width would be larger. It is well known that the gross melt fracture
(entry instability) happens at a critical wall shear stress, independent of temperature
[Kazatchkov, et al., 1995]. So, as the melt temperature is increased, flow marks occur at
higher flow front flow velocities to reach the same critical wall shear stress, i.e., Vcri
increases with the increase of the melt temperature. However, mold temperature had
little effect on the wall shear stress in our case, so the flow marks happened almost at the
same flow front velocities at different mold temperatures.
3.1.4 Conclusion
For the alternate flow marks, the effect of polymer rheology, injection speed,
mold geometry, melt temperature, mold temperature, holding pressure, injection
64
pressure, and mold surface coatings on the appearance of the alternate flow marks was
studied.
It was found that a polymer with the highest dynamic viscosity, elastic
modulus, first normal stress difference, transient extensional viscosity, and the longest
relaxation time exhibited the alternate flow marks. For the alternate dull and shiny flow
marks, flow front velocity is a very important variable. The flow marks occurred above a
critical wall shear stress, but disappeared at high injection speeds. For the wavelength
and the width of the flow marks, mold geometry or mold temperature had an effect.
However, melt temperature did not have much effect. The flow marks could be reduced
by one or more of the following factors: high injection speed, high melt or mold
temperature, mold surface coatings, and/or changing molecular weight or its distribution.
It was found that there was no difference between the crystallinity of dull regions and
shiny regions. The melt in dull regions was slightly oriented while the melt in shiny
regions was highly oriented. It was also found that coating these surfaces could not
prevent the occurrence of the flow marks, although it could alleviate them. Slip was not
the cause of the generation and disappearance of the alternate flow marks.
The
generation of the flow marks could be explained by an entry viscoelastic flow instability.
3.2 SYNCHRONOUS DULL AND GLOSSY FLOW MARKS
3.2.1 Introduction
Several types of flow marks may occur during polymer melt injection molding
processes, such as alternate dull and glossy flow marks and synchronous dull and glossy
65
flow marks. Flow marks cause aesthetic defects on the surface of molded parts, and are
very difficult to cover with paints. Because they are not well understood, much attention
has been paid to the flow marks in recent years. Although alternate dull and shiny flow
marks [Yokoi, 1994b; Chang, 1996a; Chang, 1996b; Hobbs, 1996; Heuzey, et al., 1997;
Hamada and Tsunasawa, 1996; Dharia, 1999; Bulters and Schepens, 2000; Grillet, et al.,
2000; Charmeau, et al., 2000; Xu and Koelling, 2001; Jayaraman, 2002] and wavelike
flow marks [Tredoux and Satoh, 1999; Tredoux, et al., 2000; Yokoi, et al., 1994a;
Yoshii, et al., 1993; Yoshii, et al., 1996; Lee and Mills, 1994] have been studied in
literature, little work has been undertaken to synchronous flow marks [Yokoi, et al.,
1994c; Salamon, et al., 1998]. This type of flow marks is characterized as repeated dull
and glossy regions where a dull/glossy zone on one side corresponds to a dull/glossy
zone on the other side, as shown in Fig. 3.29.
Yohoi [Yokoi, et al., 1994c] found that the gate shapes and mold surface quality
had a great effect on the generation of flow marks and the flow marks varied
dramatically with the front flow velocity. At a higher melt temperature, flow marks
become thinner. At the melt temperature of 240ºC, flow marks as well as pressure
variation did not occur. They explained that during the filling process, the gate pressure
was increased, while the melt velocity was decreased at the flow front and the melt was
cooled down. On the other hand, the gate was frozen and the flow resistance was
increased. Therefore, the melt at the flow front was accelerated with the release of the
high gate pressure, and thus the resin near the flow front underwent cooling.
Consequently, the transcription precision decreased in the subsequent fountain flow
66
process. Then the flow marks were formed. In injection molding with a center-gate,
halos similar to flow marks with synchronous dull and glossy regions were formed
[Salamon, et al., 1998]. It was found that the temperature gradient was the cause of the
formation of the halos. It was also shown that with the increase of injection rates, the
halos became more prominent and the diameter of the halos became larger.
In this paper, we study the effect of operating parameters and mold surface
coatings on flow marks of different polymer melts. Possible correlation between gross
melt fracture in extrusion and synchronous dull and glossy flow marks in injection
molding is discussed, and a possible mechanism is proposed.
3.2.2 Experimental
Molding experiments were conducted on a Sumitomo SG M-HP 180-ton
injection molding machine.
The materials used were two types of high-density
polyethylene, named HDPE1 and HDPE2. Two rectangular molds were employed with
different thicknesses (1 and 5.1 mm). The edge gates were used with a thickness of 0.5
mm for the thin mold and 2.5 mm for the thick mold. The length and width of the mold
channel was 150 and 51 mm, respectively. The melt temperature was 180, 210 and
240°C, while the mold temperature varied from 20 to 70°C. The complex viscosity,
storage and loss modulus, and first normal stress difference were measured by a
Rheometrics RMS 800.
A tensile tester, Instron 8511, was used to measure the
extensional viscosity at 100°C, based on the standard ASTM test. The samples were
standard tensile bars with 13 mm in the narrow-section width, 57 mm in total length, and
67
3.2 mm in thickness. To obtain the constant strain rate, one needs to program the Instron
machine to follow the exponential type increase of sample length. Dynamar 9613 (a 3M
product), a fluorocarbon elastomer, was used as a coating agent. Its dilute acetone
solution, ca. 1%, was coated on hot surfaces and then the solvent was allowed to
evaporate.
A Differential Scanning Calorimeter from TA Instruments, DSC 2920, was used
to measure the crystallinity of dull and shiny regions. The sample was scanned from 30
to 200°C at the rate of 10°C/min. A Scanning Electron Microscopy, Philips XL 30, was
employed to observe the morphology of dull and shiny regions. An optical profilometer,
Wyko NT330, was used to measure the roughness of the dull and shiny regions. To
exam the melt fracture phenomena, a two-stage single-screw extruder (Rheomex 252p)
from Haake was applied. The screw has a diameter of 3/4 inches and a length to
diameter ratio (L/D) of 25. A capillary die with 1.2 mm in diameter and 12 mm in
length was used. The temperature profile from front zone to the die was 100°C /125°C
/145°C /145°C. The flow rate was calculated by dividing the measured sample weight
collected by the time duration.
Because it is very difficult to estimate the wall shear stress in molding filling, CMOLD 2000 was used to simulate filling molds. First the geometry was built, then the
mesh was generated. In the simulation, processing parameters, such as shot size, V/P
switch pressure, holding pressure, holding time, cooling temperature and cooling time,
were the same as those in the real injection molding processes. After the simulation, the
wall shear stresses at the center of flow front and gates were read.
68
3.2.3 Results and Discussion
3.2.3.1 Rheological Characterization
The complex viscosity of HDPEs was measured at 180, 200 and 220°C. Fig.
3.30 shows the complex viscosity at 180°C. It was found that the complex viscosity
decreased with an increase in frequency. Fig. 3.31 shows the storage modulus and loss
modulus at 200°C. Fig. 3.32 shows the first normal stress difference N1 versus shear
rate at 180°C. It was found that HDPE1 had a larger complex viscosity, elastic modulus,
viscous modulus, and first normal stress difference than HDPE2. Fig. 4.33 shows that
the extensional viscosity vs. time at the strain rate of 0.001. It was found that HDPE1
had a larger extensional viscosity at the same strain rate.
3.2.3.2 Injection Molding Experiment
It was found through the experiment trials that both HDPEs exhibited
synchronous flow marks at certain processing conditions.
The flow marks were
generally in the phase between the top and the bottom.
Flow mark description
The flow marks occurring were characterized as synchronous dull and shiny
regions. Flow marks occurred in the thin mold only when the flow front velocity was
large. The flow marks did not occur in the thick mold. The flow marks did not occur
immediately after the gate. With an increase in the injection speed, flow marks became
69
more pronounced and continuous. When the injection speed was further increased, flow
marks became more continuous and it was difficult to distinguish different regions. The
width of the dull regions changed with the velocity of the flow front. Fig. 3.34 shows a
typical sample of flow marks for HDPE2.
Effect of operating conditions on flow marks
It was found that flow mark patterns changed as the injection speed increased.
Fig. 3.35 shows the effect of flow front velocity on the wavelength for HDPE2. It was
found that for the thin mold, the wavelength decreased with the increase of the flow
front velocity. Furthermore, the wavelength is shorter at a lower melt temperature;
nevertheless, at a higher melt temperature, the wavelength is not affected by the melt
temperature. Fig. 3.36 shows that for HDPE2 the lower the mold temperature, the
longer the wavelength. It was also found that with an increase of the mold temperature,
the flow marks were dimmer.
For the synchronous flow marks of HDPE2, the width of the dull regions was
usually very narrow, around 1-3 mm at the flow front velocity ranging from 0.4-0.9 m/s.
At a higher flow front velocity, the dull and shiny regions became irregular and mixed
together, making it very difficult to distinguish different regions. However, it was
clearly observed that the width increased with an increase of the flow front velocity.
It was found that flow marks occurred above a certain flow front velocity, Vcri. It
was further found that the mold temperature almost had no effect on Vcri. However, Vcri
increased as the melt temperature increased, as shown in Fig. 3.37. It was also found in
70
the experiment that the flow marks were less visible as the mold temperature increased.
The flow marks were almost invisible when the mold temperature was larger than 85°C.
Mold surface coating
The effect of the coating on the surfaces of the mold or gate was studied. It was
found that the coating on these surfaces could not prevent the occurrence of flow marks,
although it could alleviate the flow marks and make them dimmer. Another interesting
phenomenon is that coating on the mold surfaces did not change the Vcri, implying that
slip is not the cause of the synchronous flow marks. The reason is that coating on the
mold surface reduces the critical shear stress where the slip occurs, thus decreasing the
Vcri where the slip is triggered.
From the above discussion, we can see that for the wavelength and the width of
flow marks, injection speed is the most important factor and mold thickness plays a role.
Changing the melt temperature and mold temperature has an effect on the flow marks.
3.2.3.3 Morphology and Crystallinity
The DSC experiment showed that there was no difference observed in the
cystallinity between the dull and shiny regions for both HDPEs. From the SEM, it was
found that the polymer in the shiny region was highly oriented, but the polymer was
slightly oriented in the dull region, as shown in Fig. 3.38. This is in agreement with our
previous results for alternate flow marks and other researchers’ results [Salamon, et al.,
1998]. The measured average roughness by optical profilometer was smaller in shiny
71
regions than in dull regions, as shown in Table 3.4. The reported average roughness is
the average value of 5 randomly selected positions.
3.2.3.4 Extrusion
The HDPEs were extruded at the die temperature 145°C. It was found that above
a certain wall shear stress, sharkskin melt fracture occurred for both HDPEs. At a higher
wall shear stress, spurt flow instability occurred. At a still higher wall shear stress, gross
melt fracture occurred. The extrudate irregularity was helical. The flow curve of
HDPE2 is shown in Fig. 3.39. The average pressure was used to calculate the wall shear
stress when pressure oscillation occurred.
The wall shear stress was estimated by
∆P
without the Bagley correction, where ∆P is the pressure drop in the die, L is the
4L / D
die length, and D is the diameter of the die. The apparent shear rate was calculated by
32Q
, where Q is volumetric flow rate. Th experiment showed that the critical wall
πD 3
shear stress for the onset of sharkskin is about 0.24 MPa, and the critical wall shear
stress for the onset of the helical irregularity is about 0.51 MPa. The typical examples of
smooth surface, sharkskin, spurt flow, and helical melt fracture are shown in Fig. 3.40.
3.2.3.5 Simulation
To obtain wall shear stress during filling of the spiral molds, a simulation was
run on C-MOLD 2000. The critical wall shear stresses at the middle of the gate were
72
obtained for HDPE2 where the flow marks began to form. The processing parameters
and Vcri were determined from the injection molding experiments. Fig. 3.41 shows the
critical wall shear stress at the middle of the gate at different melt temperatures. It was
found that the wall shear stresses were very close before the F/P switch. That means the
flow marks start to form at the same wall shear stress 0.84 MPa at the gate at different
melt temperatures. Fig. 3.42 shows the critical wall shear stress at the middle of the gate
vs. the filling percentage at different mold temperatures. It shows that for the same
resin, the wall shear stress generally did not change much at different mold temperatures.
The decreasing sections of the curves in Figs. 3.41 and 3.42 were the pressure holding
stages. Short shots happened for the samples. From the simulation, it was found that
flow marks started at the same critical wall shear stress independent of melt temperature
and mold temperature.
3.2.3.6 Mechanism
The extrusion instability is associated with the appearance of distortion on the
extrudate surface, sometimes accompanied by oscillatory flow. For linear polymer melts
such as LLDPE and HDPE, when the shear stress reaches a critical value, the surface
becomes rough and wavy, and sharkskin occurs. At a higher stress, slip-stick or spurt
flow occurs. At a still higher stress, a transition region may occur where the surface is
relatively smooth with long-wavelength distortion. At much higher stress, gross or wavy
distortion occurs [Denn, 2001]. This is in agreement with our extrusion experimental
results. Although there is a disagreement about the cause of the origin of gross melt
73
fracture, most researchers agree that entry instability causes the melt fracture [Piau and
Agassant, 1996; Piau, et al., 1990; Den Otter, 1970]. The instability is also affected by
various properties, such as polymer structure, geometry of die entry, melt temperature,
and die temperature [Piau and Agassant, 1996].
For the generation of vortices and gross melt fracture, a detailed introduction can
be found in Section 3.1.3. For viscoelastic fluids, a corner vortex may occur at a low
flow rate before a contraction. The corner vortex zone is a dead zone and does not
interact with the outside fluid. The formation of vortices may be due to the increasing
extensional viscosity with the deformation rate and/or the shear-thinning effect [Denn
Otter, 1970; Cpgswell, 1972]. For some viscoelastic fluids, as a flow rate is increased, it
grows inward toward lip [Yesilata, et al., 1990]. The upstream flow is steady in this
stage. At a very high flow rate, it grows upstream, and the corner vortex fluctuates and
makes the flow field entirely unstable. For some other viscoelastic fluids, as the flow
rate is increased, two types of vortices, corner vortex and lip vortex, coexist. As the
flow rate is increased, the corner vortex and lip vortex recirculating areas expand [Piau
and Agassant, 1996; Yesilata, et al., 1999]. Then the lip vortex gradually develops and
invades the corner vortex, and finally generates a single area of recirculation. At a still
higher flow rate, the flow becomes unstable and the vortex pulsates or rotates, causing a
global change of flow structure [Boger, et al., 1986; Rothstein and McKinley, 2001]. It
was found that the development of upstream instabilities governed the appearance of the
extrudates and the helix pitch. The melt fracture occurs when the vortex is unstable.
The amplitude and frequency of pulsation increases with the pressure [Piau and
74
Agassant, 1996].
Usually the surface distortion and the frequency of the vortex
pulsation are identical.
In short, vortices may form before a contraction, and unstable vortices and gross
melt fracture are closely related. In fact, the process that polymer melts experience in
injection molding is similar to that of extrusion, as shown in Fig. 3.18. That is, the
polymer melt meets a contraction and experiences high shear stress at the die or gate,
then the polymer melt leaves the die or gate and the polymer chains relax. Thus, for
polymer melt experienced injection molding, we could logically expect that a vortex may
form and an instability may happen at the entry when the flow rate is high. The
oscillating entry instability can propagate and affect the downstream flow.
Thus
oscillating or pulsating flow may also occur in the mold, and the different history of
heating and shearing which the melt experiences generates flow marks. The different
flow marks, alternate dull and glossy flow marks and synchronous dull and glossy flow
marks, may be due to two different types of vortex instabilities, oscillating or pulsating
instability. Furthermore, the pulsating instability probably results in synchronous flow
marks. The pulsating flow makes the flow front velocity change periodically from low
to high, and it also changes the flow front melt temperature and shear stress periodically,
as shown in Fig. 3.43. Thus, this periodical changing generates synchronous flow marks
because the top and bottom are identical, i.e. in phase. Our experiment showed that both
HDPEs exhibited helical gross melt fracture at a high flow rate, so it is not surprising
that HDPEs exhibited flow marks. In fact, synchronous flow marks of HDPE2 started to
occur at the same wall shear stress independent of melt and mold temperature, implying
75
that they have the same characteristic as gross melt fracture and may have the same
origin of abnormal appearance ⎯ the entry instability.
The reason is that entry
instability for the generation of gross melt fracture in extrusion occurs at the same
critical wall shear stress level and does not changed with the die temperature
[Kazatchkov, et al., 1995].
This mechanism could explain our experimental results of flow marks. It was
found that the frequency of the flow marks increased with the increase of flow front
velocity, as shown in Fig. 3.44. The frequency was calculated by dividing the flow front
velocity by the wavelength. The trend of frequency is in a reasonable range compared to
the frequency of vortices of gross melt fracture in extrusion [Denn Otter, 1970]. We
believe that entry viscoelastic instability accounts for the synchronous dull and glossy
flow marks.
3.2.4 Conclusion
For synchronous dull and glossy flow marks, the effect of operating parameters,
mold geometry, and mold surface coatings on the flow marks was studied. Synchronous
dull and glossy flow marks occurred above a certain flow front velocity. It was also
found in the experiment that the flow marks were less pronounced as the mold
temperature increased.
It was found that there was no difference between the
crystallinity of dull and shiny regions. However, the polymer was highly oriented in
shiny region while it was slightly oriented in dull regions. It was also found that mold
surface coatings did not eliminate the flow marks. Mold surface coatings scarcely
76
changed the Vcri, meaning that slip was not the cause of the generation of the flow
marks. Extrusion experiments showed that helical gross melt fracture occurred for both
HDPEs. Finally, it was proposed that entry viscoelastic instability was the reason for the
generation of the synchronous flow marks.
77
PP-A
PP-B
PP-C
PP-D
0.223
0.447
1.382
0.548
Zero viscosity ηo (Pa.s)
915
5446
30166
7445
ηs (Pa.s)
182
619
1500
787
Relaxation time λ (s)
Table 3.1 Relaxation time and zero viscosity at 200°C
78
Polymer
PP-A
PP-B
PP-C
PP-D
Mν
128,000
142,000
121,000
164,000
Table 3.2 Viscosity-molecular weight
79
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
(nm)
(nm)
(nm)
(nm)
(nm)
Shiny
Dull
Shiny
Dull
Shiny
Dull
Shiny
Dull
Shiny
Dull
495.9
692.4
387.1
571.1
435.8
504.4
530.4
571.2
336.9
344.7
Table 3.3 Average roughness of the dull and shiny regions
80
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
(nm)
(nm)
(nm)
(nm)
(nm)
Shiny
Dull
Shiny
Dull
Shiny
Dull
Shiny
Dull
Shiny
Dull
453.8
514.1
422.0
480.6
398.8
484.8
390.8
467.1
356.3
486.3
Table 3.4 Average roughness of the dull and shiny regions
81
Dull region
λ
Dull regions are out of phase on
the top and the bottom
Fig. 3.1. Alternate dull and glossy regions.
82
1.E+05
PP-A
PP-B
Viscosity (Pa.s)
PP-C
PP-D
1.E+04
1.E+03
1.E+02
1.E-01
1.E+00
1.E+01
1.E+02
Frequency (1/s)
Fig. 3.2. Comparison of viscosity vs. frequency at 200°C.
83
1.E+05
180°C
200°C
Viscosity (Pa.s)
220°C
1.E+04
1.E+03
1.E+02
1.E-01
1.E+00
1.E+01
Frequency (1/s)
1.E+02
Fig. 3.3. Comparison of complex viscosity of PP-C at 180, 200, and 220°C.
84
Modulus G' and G" (Pa)
1.E+05
1.E+04
1.E+03
PP-A G'
PP-A G"
PP-B G'
PP-B G"
PP-C G'
PP-C G"
PP-D G'
PP-D G"
1.E+02
1.E+01
1.E+00
1.E-01
1.E+00
1.E+01
Frequency (1/s)
Fig. 3.4. Comparison of elastic and viscous modulus at 200°C.
85
1.E+02
1.E+04
N1 (PA)
1.E+03
1.E+02
PP-A 200°C
1.E+01
PP-B 200°C
PP-C 200°C
PP-D 200°C
1.E+00
0.001
0.010
0.100
1.000
Shear rate (1/s)
Fig. 3.5. First normal stress difference vs. shear rate at 200°C.
86
10.000
10000
180°C
200°C
220°C
N1 (Pa)
1000
100
10
0.001
0.010
S hear rate (1/s)
0.100
Fig. 3.6. The first normal stress difference of PP-C vs. shear rate at 180, 200, and 220°C.
87
Extensional viscosity (Pa)
1.E+09
1.E+08
PPA
PPB
PPC
PPD
1.E+07
0.1
1.0
Time (s)
10.0
Fig. 3.7. Transient extensional viscosity at 130°C.
88
100.0
1.E+04
η ', 2 η "/ω
1.E+03
1.E+02
1.E+01
1.E+00
n'
η'
2n"/w
2η"/ω
1.E-01
1.E-02
1.00E-02
η ' Giesekus
2η"/ω Giesekus
1.00E-01
1.00E+00
1.00E+01
1.00E+02
1.00E+03
Reduced frequency ωα T (1/s)
Fig. 3.8. Determination of relation time by one-mode Giesekus model.
89
a: 0.02"/s
b: 0.1"/s
c: 0.5"/s
d: 2"/s
e: 4"/s
f: 6"/s
Fig. 3.9. Flow marks of PP-C at different injection speeds.
90
Fig. 3.10. A typical example of the alternate dull and shiny flow marks.
91
18
Wavele nth
(mm)
16
14
12
10
Tmold=22°C
M old thickness: 1 mm
Tmelt=190°C
Tmelt=225°C
Tmelt=260°C
8
6
4
2
0
0
2
4
Flow front ve locity (m/s)
Fig. 3.11. Effect of melt temperature on the wavelength λ.
92
6
16
Wavele ngth
(mm)
14
12
10
8
Tmelt=190°C
M old thickness: 1 mm
Tmold=22°C
Tmold=50°C
Tmold=80°C
6
4
2
0
0
0.5
1
Flow front velocity (m/s)
Fig. 3.12. Effect of mold temperature on the wavelength λ.
93
1.5
40
Wavele ngth
(mm)
35
30
20
Thickness 1 mm
Thickness 5.1 mm
T melt=190°C
15
T mold=22°C
25
10
5
0
0
0.5
1
Flow front ve locity (m/s)
Fig. 3.13. The effect of mold thickness on the wavelength λ.
94
1.5
Width of flow marks (mm)
9
8
7
6
5
Tmold=22°C
M old thickness: 1 mm
Tmelt=190°C
Tmelt=225°C
Tmelt=260°C
4
3
2
1
0
0
2
4
6
Flow front velocity (mm/s)
Fig. 3.14. Effect of melt temperature on the width of the flow marks.
95
Width of flow marks (mm)
9
8
7
6
5
Tmelt=190°C
M old thickness: 1 mm
Tmold=22°C
Tmold=50°C
Tmold=85°C
4
3
2
1
0
0
0.5
1
Flow front velocity (mm/s)
1.5
Fig. 3.15. Effect of mold temperature on the width of the flow marks.
96
35
Width (mm)
30
25
Tmelt=190°C
Tmold=22°C
Thickness 1 mm
Thickness 5.1 mm
20
15
10
5
0
0
0.5
1
Flow front ve locity (m/s)
1.5
Fig. 3.16. The effect of mold thickness on the width of the flow marks.
97
0.25
Vcri (m/s)
0.2
T mold =22 o C
0.15
0.1
0.05
0
150
200
250
Melt tempe rature ( o C)
Fig. 3.17. The starting of the flow marks, Vcri vs. melt temperature.
98
300
10
Transition velocity (m/s)
9
8
T mold =22 o C
7
6
5
4
3
2
1
0
150
200
250
Me lt temperature (o C)
Fig. 3.18. Effect of melt temperature on the transition velocity, Vtrans.
99
300
Transition & critical velocity (m/s)
1.E+01
Vtran
1.E+00
Flow mark zone
1.E-01
Vcri
Tmold=22°C
1.E-02
150
200
250
o
Melt temperature ( C)
Fig. 3.19. Flow mark zone of PP-C.
100
300
(a) Shiny region
(b) Dull region
Fig. 3.20. Morphology of surfaces of dull and shiny regions.
101
(a) Low wall shear stress
(b) High wall shear stress
Fig. 3.21. Gross melt fracture of the PP in extrusion.
102
Wall she ar stre ss (MPa)
0.25
0.2
0.15
0.1
0.05
0
1.E+01
1.E+02
1.E+03
1.E+04
Appare nt she ar rate (1/s)
Fig. 3.22. The wall shear stress versus apparent shear rate in the extrusion.
103
Shea r stress(Mpa )
0.25
PP-A
PP-B
PP-C
PP-D
0.2
0.15
0.1
0.05
0
0
20
40
60
80
100
Fill%
Fig. 3.23. Wall shear stress vs. percentage filled in the thin spiral mold.
104
0.4
Wall Shear Stress (MPa)
0.3
0.2
Tmelt=190°C
Tmelt=225°C
0.1
Tmelt=260°C
0
20%
30%
40%
50%
60%
70%
80%
90%
100%
Filling Pe rce ntage
Fig. 3.24. The critical wall shear stress at the middle of the gate at different melt
temperatures.
105
Wall Shear Stress (MPa)
0.3
0.2
Tmold=22°C
Tmold=55°C
0.1
Tmold=80°C
0
20%
30%
40%
50%
60%
70%
80%
90%
100%
Filling Pe rce ntage
Fig. 3.25. The critical wall shear stress at the middle of the gate at different mold
temperatures.
106
die
extrudate
barrel
runner
gate
mold
Fig. 3.26. The similarity between extrusion and injection molding processes.
107
gloss
normal
dull
Cavity thickness
Flow front
Flow direction
dull
normal
gloss
Fig. 3.27. Oscillating flow generates alternate flow marks.
108
70
Frequency (1/s)
60
50
40
30
20
10
0
0
0.1
0.2
0.3
0.4
0.5
0.6
Flow front velocity (m/s)
Fig. 3.28. Frequency of the flow marks versus flow front velocity.
109
0.7
Dull region
λ
Dull regions are on the phase
on the top and the bottom
Fig. 3.29. Synchronous dull and glossy regions.
110
η∗ (Pa.s)
1.E+04
1.E+03
HDPE1
HDPE2
1.E+02
0
1 Frequency (1/s)
10
Fig. 3.30. Comparison of viscosity vs. frequency at 180°C.
111
100
G',G" (Pa.s)
1.E+05
1.E+04
HDPE1 G'
HDPE1 G"
HDPE2 G'
HDPE2 G"
1.E+03
1.E+02
0.1
1.0
10.0
Frequency (1/S)
100.0
Fig.3.31. Comparison of Elastic and viscous modulus at 180°C.
112
1.E+05
N 1 (Pa)
1.E+04
1.E+03
1.E+02
HDPE1
HDPE2
1.E+01
1.E+00
0.1
1
S hear rate (1/s)
10
Fig. 3.32. First normal stress difference vs. shear rate at 180°C.
113
100
Extensional viscosity (Pa)
1.E+10
1.E+09
1.E+08
HDPE1
HDPE2
1.E+07
0.1
1.0
10.0
100.0
Time (s)
Fig. 3.33. Extensional viscosity vs. time at 100°C.
114
1000.0
Fig. 3.34. Synchronous dull and shiny flow marks of HDPE2.
115
(mm)
Wavelength
10
9
8
7
6
5
4
3
2
1
0
Tmold=20°C
Mold thickness: 1 mm
Tmelt=180°C
Tmelt=210°C
Tmelt=240°C
0.2
0.4
0.6
0.8
Flow front velocity (m/s)
Fig. 3.35. Effect of melt temperature on wavelength.
116
1
Wavelength
λ (mm)
10
9
8
7
6
5
4
T melt =210°C
Mold t hickness: 1 mm
3
2
Tmold=20°C
Tmold=50°C
1
0
0.2
0.4
0.6
0.8
Fl ow fron t ve l oci ty (m /s)
Fig. 3.36. Effect of mold temperature on wavelength.
117
1
0.6
V cri (m/s)
0.4
0.2
0
150
200
Me lt te m pe ratu re ( o C )
Fig. 3.37. Effect of melt temperature on Vcri.
118
250
(a) Dull region
(b) Shiny region
Fig. 3.38. Morphology of dull and shiny region of HDPE2.
119
Wall shear stress (MPa)
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1.E+01
1.E+02
1.E+03
1.E+04
Apparent shear rate (1/s)
Fig. 3.39. Flow curve of HDPE2 in extrusion.
120
1.E+05
Fig. 3.40. Different extrudate irregularities at different wall shear stresses.
121
1.2
Wall Shear Stress (MPa)
1
0.8
0.6
Tmelt=180°C
Tmelt=210°C
0.4
Tmelt=240°C
0.2
0
50%
60%
70%
80%
90%
Filling Perce ntage
Fig. 3.41. Critical wall shear stress vs. percentage filled at different melt temperatures.
122
1.2
Wall Shear Stress (MPa)
1
0.8
0.6
Tmold=20°C
Tmold=50°C
0.4
Tmold=70°C
0.2
0
50%
55%
60%
65%
70%
75%
80%
85%
Filling Pe rce ntage
Fig. 3.42. Critical wall shear stress vs. percentage filled at different mold temperatures.
123
Cavity thickness
gloss
normal
dull
Flow front
fast
normal
slow
Flow direction
gloss
normal
dull
Fig. 3.43. Pulsating flow generates synchronous flow marks.
124
180
T mold=20°C
Mold thickness: 1 mm
Frequency (1/s))
160
140
Tmelt=180°C
Tmelt=210°C
Tmelt=240°C
120
100
80
60
40
20
0
0
0.2
0.4
0.6
0.8
1
Flow front velocity (m/s)
Fig. 3.44. Frequency of flow marks vs. Flow front velocity.
125
CHAPTER 4
EXPERIMENT WITH MICRO-FEATURES AND IMPROVEMENT OF
SIMULATION ACCURACY DURING THIN-WALL INJECTION MOLDING
4.1 THIN-WALL INJECTION MOLDING WITH MICRO-FEATURES
4.1.1 Introduction
Injection molding of thermoplastics with micro-features is a new field in thinwall applications. In recent years, the fabrication of polymer-based micro-components
for optical and biomedical applications has been given increasing attention in industry
and academia [Yu, et al., 2004b]. Polymer materials are favored because of their low
cost, good biocompatibility, high optical clarity, and high impact strength compared with
silicon or glass.
Micro-injection molding has the potential for economical mass-
production. It usually combines various lithography techniques and injection molding
[Weber and Ehrfeld, 1999]. Two types of micro-parts are available: micro-sized parts
and regular-sized parts with micro-features. Micro-injection molding (MIM) is the
injection molding of plastic parts with structure dimensions in the micron or sub-micron
range. The micro-features can be considered “very” thin-wall parts. The replication of
126
micro-features is an important issue and depends greatly on the size, aspect ratio and
covered area [Weber and Ehrfeld, 1999]. Furthermore, it is a challenge to simulate
micro-injection molding processes. It has been shown that standard injection molding
packages cannot describe all of the effects in micro-injection molding [Kenmann, et al.,
20002; Yu, et al., 2002]. This study focuses on thin-wall injection molding with microfeatures by experiment and numerical simulation. The filling lengths in microchannels
are simulated and compared with experimental results.
4.1.2 Experimental
A high-speed and high-pressure injection-molding machine, Sumitomo SG 180
M-HP, was used in our experiment. Two rectangular molds were employed. The mold
cavity contained not only the base plate but also the microchannels. The main lengths of
the two molds were 203 mm and 72 mm, respectively. The long rectangular thin-wall
mold was 2 mm in thickness, 203 mm in length and 50.8 mm in width, as shown in Fig.
4.1. The distance from the last channel (channel B) to the end of the main flow is 135
mm for the long mold, as shown in Fig. 4.2. The corresponding distance for the short
mold is 4 mm, as shown in Fig. 4.2. An edge gate with 3 mm in width was used for the
main flow. A disk-like mold insert with a diameter of 508 mm was installed in the mold
base. Two micro mold inserts were tested. One mold insert, including top view and side
view, is shown in Fig. 4.3. The mold insert includes six microchannels made with wireEDM. There are three separate microchannels and the other three are next to each other
127
with a distance of 100 micrometers. All channels are 500 µm deep and 100 µm wide,
giving an aspect ratio of 5. The detailed structure of a microchannel from SEM is shown
in Fig. 4.4.
Another mold insert has similar geometry but smaller width of
microchannels. The channels are 250 µm deep and 50 µm wide, giving an aspect ratio
of 5 too. Two pressure sensors made by Kistler were mounted at the position right
before and after the insert, respectively. The data acquisition system was built based on
the data acquisition board from Keithley.
The materials used were a semi-crystalline polymer, polypropylene (PP, Inspire
C703-35U, Dow Chemical), and an amorphous polymer, poly (methyl methacrylate)
(PMMA, PL 150, Plaskolite).
The melt temperature was 240°C for PMMA and
240/260°C for PP. The mold temperature was 25 and 80°C for both materials. The
holding pressures were set at 0 psi or 500 psi. The injection speed varied from 0.2 to 5
inch/s.
The complex viscosity, storage and loss modulus were measured by a
Rheometrics RMS 800. A Scanning Electron Microscope (SEM), the Philips XL 30,
was employed to observe the microchannels. An optical profilometer, Wyko NT3300,
was used to measure the filling length of the microchannels. The vertical-scanning
interferometry (VSI) mode was used to measure step heights by multiple wavelengths of
light. The profilometer basically uses the interference of light to determine the surface
shape and transmission properties. First a light source is split into two beams, then a
pattern of interferences or fringes is formed when the two beams are reflected from a test
128
surface and a reference surface and join together.
A series of fringe patterns are
generated when the test surface is scanned. The recorded fringe patterns can be mapped
[NDSU Center for Nanoscale Science and Engineering, 2003]. The non-contact Wyko
NT3300 features outstanding software and advanced automation for highly accurate,
three-dimensional surface topography measurements. Height can be measured from
Angstroms to millimeters at a resolution of 0.1 nm.
The profile of an object is
determined using interferometry instead of a stylus. Hence, the instrument is ideal for
measuring micro-structure profiles because they can be measured without destroying
their structure.
4.1.3 Experimental Results
The dynamic viscosity of PP and PMMA was measured by a Rheometrics RMS
800, as shown in Figs. 4.5 and 4.6. It was found that PP and PMMA were typical shear
thinning thermoplastics. The parts were molded for PP and PMMA under different
processing conditions. It was found that demolding was easy when the filling length in
the microchannels was small. However, demolding was difficult when the filling in the
micro channels with the width of 100 µm was deeper than 150 µm for PMMA and 300
µm for PP. In the long mold, deeper filling could be observed in the adjacent channels
than in the separated ones, and the difference might be significant. This is due to a
reduced heat loss for the melt in adjacent microchannels. However, the filling lengths
129
were almost the same in 3 separated channels. Fig. 4.7 shows a SEM picture of a
molded microstructure from PP.
The molded parts with 100 µm microchannels were examined after injection
molding with the optical profilometer, to determine the replication accuracy of microfeatures. The measured filling lengths in the separated microchannels in the long mold
against the main flow velocity for PMMA and PP are shown in Figs. 4.8 and 4.9,
respectively. The filling lengths are longer at a higher main flow velocity for both PP
and PMMA.
The molding of the microchannels is similar to thin-wall injection
molding. A high injection speed is the most efficient way to increase the flow length. A
higher mold temperature results in a longer filling length due to less flow resistance.
Furthermore, higher holding pressure generates a somewhat longer filling length,
although the effect is not significant. PP can achieve longer filling lengths than PMMA.
A complete filling can be observed for PP at a high injection speed. It should be pointed
out that at the mold temperature of 25°C, the cavity volume was not totally filled and no
packing stage occurred. However, the filling length for PP reached 500 µm. It implies
that the microchannels may be completely filled simply in the filling stage by PP. The
filling lengths in 50 µm micro mold are shown in Figs. 10 and 11. It was found that PP
can completely fill the micro channels but PMMA can fill only less than about 50 µm.
That is, it is much more difficult to fill the microchannels when the size is scaled down.
PP is much easier to fill the microchannels than PMMA.
The effect of channel location was studied, as shown in Fig. 4.12. It was
observed that the filling lengths in channels A and B in the short mold are much longer
130
than those in the long mold. Furthermore, the filling length in channel B is much longer
than in channel A in the short mold. However, there is not much difference between the
filling lengths in channels A and B in the long mold. The difference is that channel B is
much closer to the end of the mold cavity in the short mold than in the long mold, as
shown in Fig. 4.2. The recorded cavity pressure vs. filling time in the short mold and the
long mold is shown in Fig. 4.13. If we define the filling time at which the main flow
reaches the mold cavity end as tc, the pressure profile is the same before tc, and then the
pressure increases sharply in the short mold. In the short mold, more melt can be packed
into the channels and the filling lengths in channels A and B are longer than in the long
mold. Also in the short mold, the filling length in channel B is longer than in channel A
because the melt in channel B experienced a shorter cooling time. However, in the long
mold, the polymer melt needs a relatively much longer time to flow from channel B to
the end of the mold (135 mm), and the melt in both microchannels may have frozen
before the main flow reaches the mold cavity end (i.e. before the sharp pressure rise).
Therefore, the cooling time does not affect the filling lengths at different channel
locations. We define the time the polymer melt needs to advance from the channel
position to the end of the mold cavity as ∆t, representing the degree of melt freezing in
the microchannels. If we plot the dimensionless filling lengths (filling length/depth) vs.
Fourier Number α∆t/L2, the dimensionless filling lengths decrease with the increase of
Fo. All of the data merge on a single curve, covering both molds and a wide range of
main flow velocities, as shown in Fig. 4.14.
131
The effect of packing stage on filling lengths is shown in Fig. 4.15. When the
shot size is small (≤ 0.0305 m), the mold cavity is not totally filled and there is no
packing stage. When the shot size is equal or larger than 0.0307 m, the packing occurs.
Whether the packing stage occurred or not was judged by a steep increase of the
recorded cavity pressure profile and visual observation of short shots. It was found that
at the main flow velocity of 200 mm/s, the filling lengths are about 164 µm without the
packing stage at the melt temperature of 240°C, mold temperature of 25°C and zero
holding pressure; however, the filling length increases with an increase in shot size and
the filling length reaches 334 µm finally at the shot size of 0.0508 m. At the main flow
velocity of 37.5 mm/s, the filling length is about 70 µm without packing stage, but the
filling length is 200 µm with packing stage (shot size 0.0508 m). It implies that the
packing stage is very important in filling the microchannels. The effect of holding
pressure on filling lengths is shown in Fig. 4.16. It shows that the holding pressure has
some effect on filling lengths, but is not significant.
4.1.4 Simulation Results
Because the thickness of the base plate is very large compared to the
microchannels,
the
conventional
midplane
simulation
using
the
Hele-Shaw
approximation may result in a large inaccuracy. Therefore, a 2D x-z plane simulation is
applied (x is the axial flow direction and z is the thickness direction).
To save
computational cost, a hybrid model is selected and numerical codes are developed by
Liyong Yu. The cavity is divided into three regions: the upstream, the middle, and the
132
downstream region. The 1D Hele-Shaw equation is used in upstream and downstream
regions where the control volume/finite element method (CVFEM) is used to solve the
Hele-Shaw equation and the finite difference method (FDM) is used to solve the energy
equation. The 2D general momentum equation is used in the middle region where
(CVFEM) is used to solve the momentum and energy equations numerically. The hybrid
approach has 584 triangle elements and 40 1D elements. There are 21 layers in the
thickness direction. Detailed information can be found elsewhere [Yu, 2004a; Yu,
2004b].
A series of simulation were run in the long mold by Liyong Yu. Because the heat
transfer coefficient h is very difficult to determine, the melt/base plate wall interface heat
transfer coefficient h is assumed constant, h=25000 W/m2⋅K, and three different constant
melt/microchannel wall interface heat transfer coefficients are tested. Fig. 4.17 shows
that the filling lengths are greatly underpredicted for most injection speeds for PP at the
mold temperature of 25°C. This is because the heat transfers so quickly (h=25000
W/m2⋅K) that the melt near the wall freezes before the melt can enter into the
microchannel. If the main flow heat transfer coefficient is selected to be 2000 W/m2⋅K,
the polymer melt flows much deeper into the microchannel, as shown in Fig. 4.18.
Furthermore, the value of the melt/microchannel wall heat transfer coefficient also plays
an important role in predicting the filling length. It can be concluded that the heat
transfer coefficient is critical in the filling simulation of a mold with micro-features.
Next, a different boundary condition for heat transfer at the wall was further tested:
q = hx (Tm − Tw )
133
where Tm is the gapwise mean temperature and hx is the variable local heat transfer
coefficient. hx is a function of the flow field and expressed by the local Nuselt number
Nux and the hydraulic diameter Dh [Shah and London, 1978]:
hx = Nu x k / Dh
Nu x = Nu x0 ( µ b / µ w ) 0.25
⎧1.233 (x*)− 1/3 + 0.4
for x* ≤ 0.001
⎪
0
Nu x = ⎨
− 0.488 e − 245x* for x* > 0.001
⎪
⎩7.541 + 6.874 (1000x*)
x* = x /( Dh Re Pr)
where µb and µw are the bulk viscosity and the viscosity at the wall.
Using the variable heat transfer coefficient, the filling length of PP in the long
mold was predicted very well at mold temperatures of 25°C and 80°C, as shown in Fig.
4.19.
4.1.5 Conclusion
Thin-wall injection molding with micro-features was studied experimentally and
numerically. It was found that the filling lengths in microchannels are affected by
injection speed, mold temperature, and channel location. A high injection speed or high
mold temperature results in a longer filling length. Moreover, the filling lengths in the
microchannels increase with a decrease in the filling time flowing from the microchannel
to the mold cavity end. It can be concluded that the filling stage is important, the
134
packing stage is also important (especially in the short mold), and the holding stage is
not important in filling the microchannels with PP. It is more difficult to fill the smaller
microchannels. Furthermore, the filling lengths in the microchannels are simulated by a
hybrid simulation code with a combination of the momentum equation and the HeleShaw model, and compared with experimental results. The code has fewer elements and
requires less computation time.
The simulation shows that the filling lengths in
microchannels are sensitive to the heat transfer coefficients in the main flow cavity and
in the microchannel, and extra attention is needed to select the proper heat transfer
coefficient. By using a variable heat transfer coefficient, the filling length in the long
mold was predicted very well.
4.2 CAVITY PRESSURE AND ITS PREDICTION DURING THIN-WALL
INJECTION MOLDING
4.2.1 Introduction
Injection mold cavity pressure is one of the most important parameters in the
thin-wall injection molding process.
It plays an important role in determining the
molded part quality and is a good indicator of injection machine control performance
[Angstadt, 2001; Dubay, 2001]. It not only indicates the material condition in the mold
but also affects the microstructure and part quality [Macfarlane and Dubay, 2000; Gao,
et al., 1996; Gao, et al., 1996]. Cavity pressure can affect part weight, dimensions,
cosmetics, gloss, warpage, shrinkage, etc. [Bozzelli and Cardinal, 1996]. Therefore, it is
135
very important to study the effect of injection operating variables and material properties
on the cavity pressure (gradient).
Computer aided engineering (CAE) programs are commonly used today to design
a part successfully, optimize the process, and troubleshoot [Kalnin and Zluhan, 1999].
The application of CAE has the potential to reduce overall production cost and improve
part quality. However, the injection molding process is very complicated and many
operating variables and physical properties affect the mold cavity pressure. Almost all
users would prefer better accuracy of CAE simulation [Ainoya and Amono, 2001].
During thin-wall injection molding (TWIM), the prediction error in cavity pressure from
CAE simulation may reach from 50% to more than 100% and the error increases as the
parts become thinner [Chen, et al., 2000]. This error may be due to certain assumptions
and simplifications.
For example, the effect of pressure on viscosity is neglected
although it is important in high pressure thin-wall processes [Chen, et al., 2000; Amano
and Ainoya, 2000; Fasset, 1995; Mahishi, 1998]. It was found that neglecting the effect
of pressure on viscosity led to overprediction of cavity pressure, while neglecting the
juncture loss led to underprediction of nozzle pressure [Sherbelis and Friedl, 1996]. The
heat transfer coefficient in CAE packages, such as in C-MOLD and MoldFlow, is
usually taken to be a constant (default value 25,000 W/m2⋅K), but it changes with time
and operating variables. pvT-data also affect cavity pressure [Ainoya and Amono,
2001]. Cavity pressure drop was extremely overpredicted when the effect of pressure on
viscosity and juncture loss were not considered. However, Sridhar and Narh [1999]
found that the heat capacity and thermal conductivity had almost no effect on cavity
136
pressure. Another reason for the error of simulation is the lack of a high quality database
for polymers, such as heat conductivity and pvT data [Chen, et al., 2000].
In this chapter, the effect of pressure-dependent viscosity, heat capacity, heat
transfer coefficient, juncture pressure loss and pvT-data on cavity pressure and pressure
drop prediction will be studied, and the importance of each parameter will be evaluated.
Then the importance of each variable will be evaluated, and the method to improve the
prediction accuracy will also be discussed. The cavity pressure and pressure drop are
measured experimentally and compared. The study aims to improve simulation accuracy
and offer the guidance to reduce time and cost for expensive property testing.
4.2.2 Simulation
A rectangular mold with a mold thickness of 1 mm was used in the experiment,
as shown in Fig. 4.20. A representative amorphous polymer, polystyrene (PS), and a
representative semi-crystalline polymer, high-density polyethylene (HDPE), were
selected. The melt temperature was 230°C and 250°C, and the mold temperature was
60°C for the PS. The melt temperature was 300°C and 320°C, and the mold temperature
was 80°C for the HDPE. Actual molding experiments were performed on a Sumitomo
SG M-HP 180 ton injection molding machine. A data acquisition system and software
from Keithley Instruments were used to measure cavity pressure. Pressure transducers
were made by Kistler Instrument Co.
The simulation was run on a commercial FEM software, Moldflow 3.0. To
estimate the effect of each factor on cavity pressure, the Taguchi array of the simulation
137
is shown in Table 4.1. Five two-level factors were discussed: the heat capacity Cp, the
pressure-dependent viscosity ηp, the juncture loss ∆P, the heat transfer coefficient h, and
the specific volume v. Level 1 of the heat capacity was chosen as a constant heat
capacity, and level 2 of the heat capacity changed with temperature. Level 1 of the
pressure-dependent viscosity ηp neglected the effect of the pressure while level 2
included the effect of pressure. Level 1 of the juncture loss ∆P ignored the juncture loss
while level 2 considered it. Level 1 of the heat transfer coefficient used Moldflow’s
default value, 25000 W/m2⋅°C. Level 2 of the heat transfer coefficient used 1500
W/m2⋅°C according to our experience. Level 1 of the specific volume v did not include
the effect of pressure, while level 2 included effects of both temperature and pressure.
The temperature-dependent heat capacity was measured by a DSC, TA 2920, at
the heating rate of 3.33°C/s. The results are shown in Fig. 4.21.
The pvT modeling was described by a double-domain Tait equation [Chiang, et
al., 1991].
v(T,P) = v o [1 − C ln(
P
)]
(1)
vo(T)=b1m+b2m T if T>Tt
(2)
if T<Tt
(3)
B(T)
where
vo(T)=b1s+b2s T
B(T)=b3mexp(-b4m T ) if T>Tt
(4)
B(T)=b3sexp(-b4s T ) if T<Tt
(5)
138
Tt=b5+b6 P
(6)
=T-b5
(7)
T
For semi-crystalline HDPE, the additional term vt (T, P) is added for v (T, P)
which is well known as the modified Tait equation:
v(T,P) = v o [1 − Cln(
P
B(T)
)] + vt (T,P)
(8)
if T>Tt
where vt (T, P)=0
vt (T, P)=b7 exp (b8 T - b9P) if T<Tt
(9)
(10)
pvT data were given by the Moldflow database and the specific volumes are shown in
Figs. 4.22 and 4.23, respectively.
The pressure-dependent viscosity was modeled by the Cross-WLF equation
[Hieber, 1987] over a wide range of shear rates, as shown below. The parameter D3
characterizes the effect of pressure on the glass temperature T* and thus the viscosity.
η = ηo /[1 + (
ηo γ& 1-n
) ]
*
(11)
τ
where ηo = D1 exp (-
A1(T − T*)
A2 + T − T*
(12)
)
T* = D2 + D3 P
(13)
A2 = A2 + D3 P
(14)
139
The viscosity under high pressure was measured by a capillary rheometer, the
Rheomex 252p. The measured pressure drops were corrected by the Bagley correction.
Furthermore, the viscosity at low shear rates under the ambient pressure was measured
by a Rheometrics RMS 800. The viscosity for PS and HDPE is shown in Figs. 4.24 and
4.25, respectively, and the fit model parameters are shown in Table 4.2.
To consider juncture pressure loss, the Bagley correction constants C1 and C2
were chosen as Moldflow recommended. That is, C1=6.79×10-2 Pa-0.399 and C2=1.399
for HDPE, and C1=3.3×10-5 Pa-1.108 and C2=2.108 for PS.
4.2.3 RESULTS AND DISCUSSION
The simulation results were obtained for PS in the thin-wall injection molding
process. The importance of each factor is evaluated by analysis of variance (ANOVA)
[Roy, 2001]. The peak cavity pressure values and the percent influence at three different
injection speeds, 0.5, 3 and 20 inch/s, are shown in Table 4.3 when the melt temperature
is 230°C. It was found that the specific volume is the most important factor affecting the
peak cavity pressure, and its importance increases with an increase in injection speed. A
similar conclusion can be drawn when the melt temperature is 250°C, as shown in Table
4.4. It means that a large error may occur if the effect of pressure on the specific volume
is neglected and the property should be strictly measured. The discrepancy between the
cavity pressures without the effect of pressure on the specific volume and with the effect
of both pressure and temperature on the specific volume can be seen in Fig. 4.26.
140
Without considering the effect of the pressure on the specific volume, the simulation
predicts a higher peak cavity pressure and relatively lower holding pressure.
Two other important factors affecting the peak cavity pressure are the pressuredependent viscosity and the heat transfer coefficient. ANOVA shows that both the heat
transfer coefficient and the pressure-dependent viscosity are significant factors when the
injection speed is low. It also shows that the percent influence of the heat transfer
coefficient is higher than that of the pressure-dependent viscosity, as shown in Tables
4.3 and 4.4. However, our previous simulation [Xu and Koelling, 2003] showed that the
effect of pressure on the viscosity is relatively more important than deciding the proper
heat transfer coefficient when the injection speed is high at lower melt temperatures. It
implies that the percent influence of the heat transfer coefficient and the pressure
dependent viscosity depends on both melt temperature and injection speeds. The percent
influence of the heat transfer coefficient and the viscosity decreases with the increase of
injection speeds. By including the effect of pressure on the viscosity, a higher peak
cavity pressure and a lower holding pressure are predicted, as shown in Fig. 4.27. Using
h=1500 W/m2.°C predicts a lower peak cavity pressure and a holding pressure that is
lower at first and then higher, as shown in Fig. 4.28. However, these two parameters are
very difficult to measure. Sherbelis and Friedl also predicted lower cavity pressure when
the effect of pressure on viscosity was considered [Sherbelis and Friedl, 1996].
The least important factors considered here are the heat capacity and the juncture
loss. The percent influence is very small, as shown in Tables 4.3 and 4.4. From Figs.
4.29 and 4.30, it can be seen that the heat capacity and the juncture loss have almost no
141
effect in this case. However, Table 4.3 shows that the contribution of the heat capacity
to cavity pressure increases at high injection speeds, which is usually true in thin-wall
injection molding. For heat capacity, it is very difficult to get the “true” value because
the cooling rate is very fast in thin-wall injection processes, such that common
instruments cannot scan samples fast enough. At a higher melt temperature of 250°C,
the percent influence of each factor, as shown in Table 4.4, is similar as the melt
temperature of 230°C. Sridhar and Narh [1999] also found that thermal conductivity and
heat capacity had almost no effect on cavity pressure. Other researchers also found that
a tabulated heat capacity led to a slightly higher cavity pressure drop [Ainoya and
Amono, 2001].
The simulation results of peak cavity pressure for HDPE were also obtained. The
percent influence of each factor at two different melt temperatures, 300°C and 320°C, is
shown in Table 4.5.
It was found that the specific volume and the heat transfer
coefficient are significant factors. The specific volume has the largest percent influence,
but pressure-dependent viscosity also has a relatively large percent influence compared
to the effect of the heat capacity and juncture loss.
The simulation implies that a large error may occur if the effect of pressure on
the specific volume and/or the viscosity is neglected, and/or the heat transfer coefficient
is not properly determined. These values should be carefully determined before running
simulation. The juncture loss and the heat capacity do not play a significant role in this
case.
Thus full attention needs to be given to the specific volume, the pressure
dependent viscosity, and the heat transfer coefficient when the material property model
142
is selected for simulation, and less effort should be given in determining the heat
capacity and the juncture loss.
The maximum cavity pressure drops were simulated for PS. As shown in Tables
4.6 and 4.7, the percent influence of the heat transfer coefficient is the largest among the
five factors under study, so the most important factor affecting cavity pressure drop is
the heat transfer coefficient. Generally speaking, the percent influence of the viscosity
and the specific volume are high, and the juncture loss is not a significant factor.
Furthermore, it is interesting to note that the heat capacity is not a significant factor
when the injection speed is low, but its percent influence increases dramatically with an
increase in the injection speed. However, it shows that the percent influence of the
viscosity decreases with an increase in the injection speed. For the pressure drop of
HDPE, it was found that the heat transfer coefficient and the viscosity have a high
percent influence, as shown in Table 4.8. However, the heat capacity, the juncture
pressure loss, and the specific volume have almost no effect. The influence of the
material property model is apparently different for different polymer structures. This
also implies that the specific volume, the pressure dependent viscosity and the heat
transfer coefficient generally play important roles in the maximum cavity pressure drop
and these properties need to be carefully tested before running simulations.
Furthermore, the heat capacity may be important when a very high injection speed is
applied.
The actual cavity pressure and pressure drop were also measured. Fig. 4.31
shows the pressure profiles right after the gate and at the end of the cavity at an injection
speed of 76.2 mm/s. It was found that higher peak pressures both after the gate and at
143
the end of the cavity were detected when the melt temperature was lower, due to a higher
flow resistance. Moreover, the pressure drops more rapidly when the melt temperature is
lower because the melt cools down more rapidly. Fig. 4.32 shows the pressure profiles
right after the gate at the melt temperature of 230°C under different injection speeds. It
was found that a higher injection speed caused a lower peak cavity pressure. This agrees
with other researchers’ observations in the thin-wall injection molding process [Chen, et
al., 2000; Bozzelli, et al., 1997; Fierens and Mertes, 1998]. Moreover, the pressure
drops more slowly when the injection speed is higher, probably because of the short
cooling period at the filling stage and the high viscous heating. Fig. 4.33 shows the
pressure profiles at the end of the cavity under the melt temperature of 230°C under
different injection speeds. It was found that the peak pressure increases with an increase
in the injection speed, but the peak pressure drops a small amount when the injection
speed is further increased from 76.2 to 508 mm/s. Fig. 4.34 shows the measured cavity
pressure vs. time right after the gate at the low injection speed of 12.7 mm/s. The
simulation results from different material property models are also shown in this figure.
It was found that Moldflow predicts the filling stage fairly well, but there is a large
difference in the holding stage. It can be seen that neglecting the effect of pressure on
the specific volume caused a large difference in the peak cavity pressure. Furthermore,
the predicted pressure curve including the effect of pressure on the specific volume and
the viscosity (the solid triangles) is closest to the measured pressure curve at the holding
stage compared to other predicted curves. At a high injection speed of 508 mm/s,
Moldflow overpredicts the cavity pressure at both the filling stage and the holding stage,
as shown in Fig. 4.35. Neglecting the effect of pressure on the specific volume leads the
144
largest peak cavity pressure difference between the simulation and measurement, with a
difference of about 66%. The predicted pressure curve including the effect of pressure
on the specific volume and the viscosity (the solid triangles) is closest to the measured
pressure curve at the holding stage, compared to other predicted curves. Unlike the low
injection speed, Moldflow predicts the trend of the cavity pressure well at the holding
stage, but the predicted curve shifts upward from the experimental pressure curve. The
measured maximum cavity pressure drop is 38.9 MPa; however, the predicted pressure
drop is in the range of 46-50 MPa depending on the material property models used. It
can be seen that to obtain good simulation results, the effect of pressure on the specific
volume and the viscosity must be included, and the default value of the heat transfer
coefficient must be re-evaluated. At high injection speeds, good agreement cannot be
obtained regardless of the property models selected. The reasons are out of the range we
are considering. The possible reasons are: a discrepancy between the set operating
variables and the actual values the machine reached; an inefficiency in the property
models (e.g., a property measured under equilibrium is used to simulate a nonequilibrium injection molding process); and/or the software itself due to simplifications.
4.2.4 CONCLUSION
For the thin-wall injection molding processes, it is very important to use proper
material property models when running simulations. It was found that the effect of
pressure on the specific volume is the most important factor to predict the peak cavity
pressure. The effect of pressure on the viscosity and the heat transfer coefficient is also
significant.
The heat capacity and the juncture loss are relatively less important
145
compared to other factors considered here. It was also shown that the significant factors
are somewhat different to predict maximum cavity pressure drop. The heat transfer
coefficient is the most important factor, but in general the specific volume and the
viscosity are still important. At a high injection speed, the simulation overpredicted the
peak cavity pressure and the maximum cavity pressure drop, and good prediction cannot
be achieved. Further study is necessary to understand why this happens and how to
improve the simulation accuracy at very high injection speeds. However, the differences
between the measurements and the simulations are smaller at low injection speeds in our
case.
146
No.
1
2
3
4
5
6
7
8
Cp
1
1
1
1
2
2
2
2
η
1
1
2
2
1
1
2
2
∆P
1
1
2
2
2
2
1
1
Symbol
Cp
η
1
Constant
D3=0
∆Pjuncture
C1=0
C2=0
25,000 W/m2⋅K
No effect of
pressure
h
v
h
1
2
1
2
1
2
1
2
v
1
2
1
2
2
1
2
1
2
Variable
PS: D3=1.51E-7
PE: D3=9.21E-8
PS: C1=3.3E-5, C2=2.108
PE: C1=0.0679, C2=1.399
1,500 W/m2⋅K
Effect of pressure is
considered
Table 4.1 Orthogonal array of the simulation
147
Material
τ∗ (Pa)
N (-)
D1 (Pa.s)
D2 (K)
D3(K/Pa)
A1 (-)
A 2 (K)
PS
38264
0.177
2.72E13
368
1.51E-7
31.0
51.6
PE
2791
0.542
8.86E13
256
9.21E-7
26.0
51.6
Table 4.2 Coefficients of Cross-WLF equation
148
No.
Cp
ηp
∆P
h
v
1
1
1
1
1
1
Peak P (MPa)
0.5”/s 3”/s
20”/s
84.07 72.28 72.95
2
1
1
1
2
2
56.64 48.66
51.2
3
1
2
2
1
1
91.78 75.98
75.21
4
1
2
2
2
2
60.35 51.11
51.52
5
2
1
2
1
2
66.9
54.71
54.09
6
2
1
2
2
1
74.78 68.65
73.44
7
2
2
1
1
2
72.91 55.51
54.35
8
2
2
1
2
1
78.8
74.2
70.61
Percent Influence (%)
Injectio
n speed
Cp
ηp
∆P
h
v
Significant
Factors
0.5”/s
0
5.64
0
25.77
67.28
η, h, v
3”/s
0
1.18
0.13
5.79
92.60
η, h, v
20”/s
0.32
0.12
0
0.48
98.71
v
Table 4.3 Relative influence of each factor on peak cavity pressure
at different injection speeds at 230°C
149
Percent Influence (%)
Injectio
n speed
Cp
ηp
∆P
h
v
Significant
Factors
0.5”/s
0
4.27
0
24.73
70.09
η, h, v
3”/s
0
0.89
0.03
6.32
92.59
η, h, v
20”/s
0.20
0.13
0.03
0.66
98.69
v
Table 4.4 Relative influence of each factor on peak cavity pressure
at different injection speeds at 250°C
150
Percent Influence (%)
Temperatur
e
300°C
320°C
Cp
ηp
∆P
h
v
0
5.81
0
27.14
61.72
0
6.39
0
28.44
58.98
Significant
Factors
v, h
v, h
Table 4.5 Relative influence of each factor on peak cavity pressure
at different melt temperatures for HDPE at 0.5”/s
151
Percent Influence (%)
Injectio
n speed
Cp
ηp
∆P
h
v
Significant
Factors
0.5”/s
0
11.49
0
82.98
2.82
η, h
3”/s
0.07
7.96
0
88.94
0
h
20”/s
21.56
2.22
0.10
69.64
6.20
Cp, η, h, v
Table 4.6 Relative influence of each factor on maximum pressure drop
at different injection speeds at 230°C
152
Percent Influence (%)
Injectio
n speed
Cp
ηp
∆P
h
v
Significant
Factors
0.5”/s
0.06
8.99
0
86.78
2.55
η, h
3”/s
1.14
5.35
0
93.27
0
Cp, η, h
20”/s
21.56
1.74
0.32
67.54
7.40
Cp, h, v
Table 4.7 Relative influence of each factor on maximum pressure drop
at different injection speeds at 250°C
153
Percent Influence (%)
Temperature
Cp
ηp
∆P
h
v
Significant
Factors
300°C
0
8.11
0
88.23
0
h
320°C
0
7.48
0
87.94
0
h
Table 4.8 Relative influence of each factor on maximum cavity pressure drop
at different melt temperatures for HDPE at 0.5”/s
154
Fig. 4.1. The long rectangular mold base with a disk-like insert.
155
Long mold A
Short mold
B
135 mm
A
B
4 mm
Fig. 4.2. The rectangular mold bases with a disk-like insert.
156
A
A
View A-A
Fig. 4.3. The disk-like mold insert which contains microchannels.
157
Fig. 4.4. SEM picture of the a microchannel.
158
1.E+04
180°C
Viscosity (Pa.s)
200°C
220°C
1.E+03
1.E+02
1.E-01
1.E+00
1.E+01
Frequency (1/s)
Fig. 4.5. Dynamic viscosity of polypropylene.
159
1.E+02
1.0E+04
Complex viscosity (Pa.s)
210°C
220°C
230°C
1.0E+03
1.0E+02
0.10
1.00
10.00
Frequency (1/s)
Fig. 4.6. Dynamic viscosity of polypropylene
160
100.00
a. Top view
b. Side view
Fig. 4.7. SEM of a micro-channel.
161
300
Channel Height (Micormeter)
80°C; HP=500 PSI
250
80°C; HP=0 PSI
200
150
100
50
0
0.001
0.01
0.1
1
10
Main Flow Velocity (m/s)
Fig. 4.8. Measured filling lengths in microchannels for PMMA in the long mold.
162
600
80°C; HP=500 PSI
Channel Height (Micormeter)
500
80°C; HP=0 PSI
25°C; HP=0 PSI
400
300
200
100
0
0.001
0.01
0.1
1
10
Main Flow Velocity (m/s)
Fig. 4.9. Measured filling lengths in microchannels for PP in the long mold.
163
50
45
Filling length ( m)
40
µ
80°C; HP=500 PSI
80°C; HP=0 PSI
35
30
25
20
15
10
5
0
0.01
0.1
1
Main flow velocity (m/s)
10
Fig. 4.10. Measured filling lengths in microchannels for PMMA in the long mold.
164
300
80°C; HP=0 PSI
Filling length ( m)
250
25°C; HP=0 PSI
µ 200
150
100
50
0
0.001
0.01
0.1
1
Main flow velocity (m/s)
10
Fig. 4.11. Measured filling lengths in microchannels for PP in the long mold.
165
700
Channel Height (Micormeter)
600
Short Mold, Channel A
Short Mold, Channel B
Long Mold, Channel B
500
400
300
200
100
0
0.001
0.01
0.1
1
10
Main Flow Velocity (m/s)
Fig. 4.12. Measured filling lengths in microchannels for PP in the short mold.
166
Fig. 4.13. The cavity pressure profile in the long mold and the short mold.
167
1.2
Filling length / Depth
1
0.8
0.6
0.4
100 microns, Short B
100 microns, Short A
0.2
100 microns, Long A, B
0
0.01
0.1
1
10
100
Fo
Fig. 4.14. The filling length vs. Fourier number.
168
1000
80
Cavity pressure (MPa)
70
60
50
40
Start of packing
30
20
10
0
025.40
27.94
4
30.48
8
30.73
12
30.99
16
34.29
20
50.80
24
400
350
201 mm/s
Filling length ( m)
300
µ
250
Start of packing
200
150
100
50
0
25.40
27.94
30.48
30.73
30.99
34.29
50.80
Shot size (mm)
Fig. 4.15 The effect of packing stage on filling lengths.
(Melt temperature 240°C, mold temperature 25°C, main flow velocity 0.2 m/s)
169
450
Main flow velocity 201 mm/s
400
Filling length (µm)
350
300
250
200
150
100
50
0
0
500
1000
1500
1900
Hold pressure (psi)
Fig. 4.16 The effect of holding pressure on filling lengths.
(Melt temperature 240°C, mold temperature 25°C, main flow velocity 0.2 m/s)
170
600
Filling length (micron)
Expr.
500
h=500
400
h=2000
h=2500
300
200
100
0
1
10
100
1000
10000
Main flow velocity (mm/s)
Fig. 4.17. Comparison of the filling lengths between the simulation and experiment with
constant heat transfer coefficients. Main flow heat transfer coefficient=25000 W/m2.K.
171
600
Expr.
Filling length (micron)
500
h=500
h=2000
400
h=25000
300
200
100
0
1
10
100
1000
10000
Main flow velocity
Fig. 4.18. Comparison of the filling lengths between the simulation and experiment with
constant heat transfer coefficients. Main flow heat transfer coefficient=2000 W/m2.K.
172
Filling length (micron)
600
500
Expr. Tm =25C
Sim u. Tm =25C
400
Expr. Tm =80C
Sim u. Tm =80C
300
200
100
0
1
10
100
1000
10000
Main flow velocity (mm/s)
Fig. 4.19. Comparison of the filling lengths between the simulation and experiment with
variable heat transfer coefficient.
173
P transducer
P transducer
50.8 mm
P transducer
76.2 mm
152.4 mm
Fig. 4.20. Schematic of the mold with thickness of 1 mm.
174
12000
PS
10000
8000
o
Cp (J/kg. C)
HDPE
6000
4000
2000
0
0
50
100
150
200
o
T ( C)
250
300
Fig. 4.21. Heat capacity of HDPE and PS.
175
350
1.5
0 M Pa
3
Specific volume (cm/g)
1.4
50 M Pa
100 M Pa
150 M Pa
1.3
1.2
1.1
1.0
0.9
273
323
373
423
473
Temperature (K)
Fig. 4.22. Specific volume of HDPE.
176
523
1.10
0 M Pa
1.05
100 M Pa
150 M Pa
3
Specific volume (cm/g)
50 M Pa
1.00
0.95
0.90
273
323
373
423
Temperature (K)
Fig. 4.23. Specific volume of PS.
177
473
523
1.E+05
180°C
200°C
220°C
1.E+04
Viscosity (Pa.s)
180C Fit
200C Fit
220C Fit
1.E+03
1.E+02
1.E+01
1.E-01
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
Shear Rate/Frequency (1/s)
Fig. 4.24. Experimental and fit viscosity vs. shear rate/ frequency for PS.
178
1.E+05
160°C
180°C
200°C
160°C Fit
180°C Fit
200°C Fit
Viscosity (Pa.s)
1.E+04
1.E+03
1.E+02
1.E+01
1.E-01
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
Shear Rate/Frequency (1/s)
Fig. 4.25. Experimental and fit viscosity vs. shear rate/ frequency for HDPE.
179
90
Effect of pressure not considered
Pressure-dependent v
Cavity Pressure (MPa)
80
70
60
50
40
30
20
10
0
0
2
4
6
8
Time (s)
Fig. 4.26. Comparison of cavity pressure with/without the effect of pressure on
specific volume.
180
80
Effect of pressure not considered
Pressure-dependent viscosity
Cavity Pressure (MPa)
70
60
50
40
30
20
10
0
0
1
2
3
4
5
6
7
Time (s)
Fig. 4.27. Comparison of cavity pressure with/without the effect of pressure on
viscosity.
181
80
h=25000
h=1500
Cavity Pressure (MPa)
70
60
50
40
30
20
10
0
0
2
4
6
8
Time (s)
Fig. 4.28. Comparison of cavity pressure with different heat transfer coefficients.
182
80
Constant Cp
Temperature-dependent Cp
Cavity Pressure (MPa)
70
60
50
40
30
20
10
0
0
2
4
6
8
Time (s)
Fig. 4.29. Comparison of cavity pressure with constant Cp and temperaturedependent Cp.
183
80
No juncture loss
Juncture loss included
Cavity Pressure (MPa)
70
60
50
40
30
20
10
0
0
2
4
6
8
Time (s)
Fig. 4.30. Comparison of cavity pressure with/without juncture loss.
184
80
Pressure after Gate, 250°C
Pressure at End, 250°C
Pressure after Gate (230°C)
Pressure at End (230°C)
70
Pressure (MPa)
60
50
40
30
20
10
0
0
2
4
6
8
10
12
14
16
18
Time (s)
Fig. 4.31. Pressure profiles right after the gate and at the end of the cavity at the
injection speed of 76.2 mm/s and the melt temperature of 230 and 250°C.
185
80
12.7 mm/s
76.2 mm/s
508 mm/s
70
Pressure (MPa)
60
50
40
30
20
10
0
0
2
4
6
8
10
12
14
Time (s)
Fig. 4.32. Pressure profiles right after the gate at the melt temperature of 230°C with
different injection speeds.
186
40
12.7 mm/s
76.2 mm/s
508 mm/s
35
Pressure (MPa)
30
25
20
15
10
5
0
0
2
4
6
8
10
12
14
Time (s)
Fig. 4.33. Pressure profiles at the end of the cavity at the melt temperature of 230°C
with different injection speeds.
187
90
Experimental pressure
Effect of pressure on v not considered
P-independent viscosity
Pressure-dependent viscosity
h=1500
80
Cavity Pressure (MPa)
70
60
50
40
30
20
10
0
0
2
4
Time (s)
6
8
Fig. 4.34. Comparison of experimental and predicted pressure drop at the injection
speed of 12.7 mm/s.
188
90
Experimental pressure
Cavity Pressure (MPa)
80
Effect of P on v not considered
P-independent viscosity
70
P-dependent viscosity
h=1500
60
50
40
30
20
10
0
0
2
4
6
8
Time (s)
10
12
14
Fig. 4.35. Comparison of experimental and predicted pressure drop at the injection
speed of 508 mm/s.
189
CHAPTER 5
CHARACTERIZATION OF VIRGIN/POST-CONSUMER BLENDED
HIGH IMPACT POLYSTYRENE RESINS FOR INJECTION MOLDING
5.1 INTRODUCTION
Plastics have become a common materials choice in many new products and
millions of kilograms of plastics are used annually [Society of the Plastics Industry,
2001]. The attention paid to polymer recycling has increased in the past decade because
more efficient re-use of materials will reduce the quantities of plastics sent to landfills as
well as reduce raw material extraction.
Furthermore, the advent of “take-back”
legislation accelerates waste prevention practices [Gamalski, 1996; Meffert and
Kirchgeorg, 1997; Hubschman, et al., 1995]. However, only a small amount of plastics
is reused as introduced in Section 2.1. Reducing virgin resin consumption can be
achieved by reduction of material requirement or resin recycling. One strategy is to use
thinner wall molding to reduce the quantity of material required. However, thin-wall
molding requires high injection speed, high injection pressure with polymers that could
190
withstand high shear rates and possible molecular degradation. Another strategy is to
recycle resin. In this study, we focus on resin cycling. However, how to characterize the
post-consumer resin (PCR) and how to increase the percentage of the post-consumer
resin are two of the problems in recycling plastic.
Currently, only less than one percent of HIPS is recovered from the total 19%
market share [Dillon and Aqua, 2000]. Two big challenges to reuse post-consumer resin
are material contamination and degradation.
Post-consumer polymers may be
contaminated from other materials [Langerak, 1997]; post-consumer products may
contain polymer blends as well as additives such as reinforcements, paint, or flame
retardants [Dillon, 1999].
Another challenge is the material degradation because
returned polymers have been exposed to various thermal and mechanical conditions.
Thus, molders are reluctant to use recycled plastics because extensive experimental
testing is required to identify plausible use and determine molding parameters.
Recyclers currently select between options such as incineration or downcycling.
The major problem to reuse PCR is that polymer databases do not contain
information about PCR. Beside the material selection assistance, polymer databases are
used in mold filling simulation to design, reduce experimental time to decide processing
parameters, and predict possible problems.
If molders must use trial and error to
determine PCR molding parameters, then a higher setup time is required for PCR than
for a virgin resin that is included in the database. Manufacturers usually use virgin resin
191
databases to decide processing parameters to reduce time because molders cannot easily
decide them without the material characterization of PCR.
Therefore, our initial investigation began with characterization of the postconsumer resin. The viscosity is one of the basic properties for the reuse of the postconsumer resin. The melt viscosity of the post-consumer resin was measured and the
virgin resins were identified with the same melt viscosity as the PCR. Next, the melt
viscosities of post-consumer and virgin resin blends were measured.
Then the
mechanical properties of blends were measured and the effect of different virgin resins
and weight percentage of virgin resins were discussed. This investigation helped us
evaluate the viability of reusing the PCR in new injection molded products. Our goal is
to characterize the relationship between the ratio of recycled content to virgin content
and the mechanical properties. The mechanical properties, including tensile properties,
flexural properties, and impact properties, of the blends with different percentages of
reuse resin were analyzed through experiments.
Furthermore, we investigated the
molecular weight and morphology of molded parts to help explain and predict the
properties of recycled blends for injection molding. Understanding the relationship
between rheological and design characteristics will provide both suppliers (recyclers)
and customers (molders) with valuable insights regarding viable uses for post-consumer
resins. Meanwhile, we introduce a sequence of steps to obtain PCR input for mold
filling simulation.
The purpose is to reduce the amount of experimental time to
determine molding parameters. The method is tested by molding ASTM specimens and
a thin-wall application in film canisters.
192
5.2 EXPERIMENTAL
5.2.1 Characterization of Material
It is important to identify the post-consumer polymer properties. In general, it is
nearly impossible to identify the original resin manufacturer for post-consumer polymers
in electronics equipment. In our case, we only knew the polymer was labeled HIPS (high
impact polystyrene); we did not know the original resin manufacturer or product code.
Therefore, we tested the rheological properties of the PCR in order to identify the most
suitable "virgin resin” for the blends. The PCR material we used consisted of ground
pieces of printer and monitor housings.
The size of the fragments was greater than 100 mm. The incoming fragments
were inspected manually for metal contamination and then were shredded again to reduce
their size before mixing with virgin resins. The maximum dimension of the shredded
fragments was 1-10 mm, which was close to the size of the virgin resins.
The rheometer used was a Rheometrics Mechanical Spectrometer (RMS 800).
The rheological properties of the blends which consisted of different percentages of postconsumer HIPS and virgin resins were also studied at three temperatures: 180ºC, 200ºC,
and 220ºC. Molded discs were used for the measurement of viscosity for the blends.
5.2.2 Measurement of Molecular Weight
The molecular weight was measured by GPC (Gel Permeation Chromotography).
The samples used were molded blends with 0%, 50%, and 100% Huntsman PS 702,
193
molded blends with 50% and 100% Nova PS 3350, and never molded, 100% virgin Nova
PS 3350. The solution was prepared by dissolving blends in THF (Tetrahydrofuran).
Each sample was analyzed twice with a running time of 45 minutes and an injection
volume of 200 µl. We report the average of the two runs in Table 5.1.
5.2.3 Microscopy and Spectroscopy
For the morphological measurement, the aim is to observe the dispersion of
rubber phase in polystyrene and the size of rubber domains because the rubber particles
can affect the mechanical properties. A Philip XL-30 FEG environmental scanning
electron microscope (ESEM) was used. The sample was stained by 1% OsO4 aqueous
solution for 15 days and carbon-coated for morphological measurements. The fracture
surfaces were observed with 15 KV power. The magnification in this study varied from
200x to 10,000x.
The purpose of the Raman spectroscopy tests is to determine if there is a
detectable difference in the absorption spectra for the PCR and the virgin high impact
polystyrene. The virgin resin Huntsman PS 702 was used in the experiment. The
infrared vibrational spectra were obtained using a Bruker Equinox 55 with IR Scope 1.
The instrument was operated in reflectance mode using the 15x microscope objective and
4 cm-1 resolution. OPUS software, version 2.2, was used for instrument control and data
handling.
The Raman vibrational spectra were obtained using a Chromex Raman 2000
spectrometer upon illumination by a 785 nm diode laser DSL and imaged on a
194
Photometrics 1024 X 256 pixel red enhanced CCD detector. The spectra were taken at a
180° collection angle with a depth of focus of several mm. The laser power was typically
50 mW with a spot size of 80 µm.
5.2.4 Processing Parameters for ASTM Specimens
To determine initial processing parameters, a mold filling simulation was run on
C-MOLD 97.7. C-MOLD is a set of integrated computer aided engineering (CAE)
simulations for plastics molding processes, including injection mold filling, post-filling,
cooling, part shrinkage and warpage.
C-MOLD provides recommendations for
processing parameters such as fill time, inlet and melt temperature. CAE provides an
easy-to-use data visualizer for viewing mesh information and analysis results.
C-MOLD 97.7 was used to simulate filling our mold with one of the virgin resins,
Huntsman PS 702, which had the same viscosity versus shear rate as our PCR. The
ASTM mold consisted of six cavities, including two tensile bars, two sheets and two
discs.
From the results of the mold simulation and several experimental trials, the
operating parameters, such as inlet melt temperature, melt temperature, and cooling time,
were selected to injection mold ASTM specimens.
The mold filling simulation required input for the resin properties. They can be
obtained from commercial resin databases or resin suppliers. However, resin databases
only contain virgin resin. So, we identified a virgin resin with similar viscosity to use as
input. In our approach, recyclers do not need to know the original resin manufacturers or
195
product codes. We assume that the PCR has been processed and sorted by manual
disassembly [Meacham, et al., 1999] or new bulk recycling methods [Arola and Biddle,
2000] so that it is not contaminated by other materials.
5.2.5 Physical Properties of ASTM Specimens
Six different weight percentages of blends were prepared, as shown in Table 5.2.
Two selected virgin resins, Huntsman PS 702 and Nova PS 3350, were used. These
virgin resins were selected because they had the close viscosity versus shear rate curve as
the PCR. The blends were mixed for one minute in a Little Ford Lodige Precision Mixer.
The ASTM specimens were prepared with a 50 ton Sumitomo injection molding
machine. The virgin material and post-consumer resin were mixed completely and then
were dried at 160ºF for 2 hours prior to injection molding. According to the results of the
mold design, the barrel temperature was set from 380ºF to 440ºF from the rear zone to
front zone. The mold temperature was kept at 77ºF.
For blends with Huntsman PS 702, the physical properties tested include: tensile
strength and modulus (ASTM D 638) at 23.3ºC and humidity 21%, flexural strength and
modulus (ASTM D 790) at 18.4ºC and humidity 12%, and notched Izod impact strength
(ASTM D 256) at 18.4ºC and humidity 21%. For blends with Nova PS 3350, all tests
were performed at 27.3ºC and humidity 30%.
Roughness and waviness measure the small-scale surface irregularities.
Roughness represents the range of groove heights of the surfaces while waviness is the
regression line (mean line) of the roughness profile. Two surface parameters, roughness
196
average (Ra) and waviness average (Wa) were measured. According to ISO, ANSI, and
DIN standards, Ra is the arithmetic average deviation of the roughness profile from the
roughness centerline, while Wa is the arithmetic average deviation of the waviness profile
from the waviness centerline [Sander, 1991].
The test was performed using the
Perthometer with a Gaussian filter type. The tests were conducted with a straight line
(entire trace) tilt correction and an evaluation range of 4.00 mm. One data point was
collected at each of five locations on each of three ASTM impact discs per blend for a
total of fifteen data points per blend.
5.2.6 Application
The ASTM test specimen mold is specially designed to minimize material
damage during molding. So, we tested the recycled material under high shear stress
condition to assess the ability of the material to withstand more realistic industrial use.
The film canister mold, loaned by Eastman Kodak Company, was used to test the postconsumer/virgin polymer blends and is a thin-wall application compared to the original
printer and monitor housings. The film canister is shown in Fig. 5.1. The canister base
has variations in thickness as well as the recycling logo. In Table 5.3, the mold design
characteristics are listed.
C-MOLD 97.7 was used to simulate filling the film canister mold with the virgin
resin, Huntsman 702. From the results of simulation, combined with experimental trials,
the operating parameters, such as inlet melt temperature, melt temperature, cooling time,
etc., were selected for making film canister specimens, as reported in section 5.3.6. At
197
the same operating parameters, six types of blends of different percentage of PCR were
used to mold canisters. In order to compare the two virgin resins, we processed blends
under the same conditions. However, Nova PS 3350 has a lower melt index of 0.27
g/min compared to the Huntsman PS 702 melt index of 0.75 g/min [IDES, 1999]. Thus,
we used a higher injection velocity for virgin Nova PS 3350 after several experimental
runs.
One of the quality indicators tested for the canisters was the tensile strength. The
specimens consisted of strips of uniform width and thickness. According to ASTM
standards, we chose 100 mm as the width with a thickness less than 0.8 mm. Since the
thickness of the canister wall was less than 1 mm, the ASTM D-882-97 was adjusted
slightly by shortening the length of the specimens from 101.6 to 98 mm and 46 mm. To
ensure uniform width, calipers with 0.25 mm capability were used to check the specimen
width. The utmost care was exercised in cutting specimens to prevent nicks and tears that
may cause premature failure. To eliminate the anisotropic effect of the material, two sets
of test specimens were prepared having their long axes parallel with and normal to the
flow direction. The flow direction of the material in injection molding was from the
bottom to top.
5.3 RESULTS AND DISCUSSION
5.3.1 Characterization of Material
The rheological properties of the ground post-consumer HIPS were studied at
three temperatures: 180°C, 200°C, and 220°C. Fig. 5.2 is the viscosity versus frequency
198
curve of the post-consumer material at 220°C. We identified two virgin resin candidates,
Huntsman PS 702 and Nova PS 3350, in the C-MOLD resin databases by comparing the
viscosity curves.
The viscosity of blends of different percentage of the recycled resins was also
investigated at three temperatures: 180ºC, 200ºC and 220ºC. Figs. 5.3 and 5.4 show the
viscosity of blends with Huntsman PS 702 or Nova PS 3350 versus frequency at
approximately 200ºC, respectively. It is found that all blends are shear thinning. It is also
shown that the viscosity increases with the increase of the percentage of the PCR.
5.3.2 Molecular Weight
The molecular weights are listed in Table 5.1. It is shown that molecular weight
and polydispersity of blends with Huntsman PS 702 increase with the increase of the
percentage of Huntsman PS 702. However, for blends with Nova PS 3350, the molecular
weight decreases with the increase of the percentage of Nova PS 3350, though the
polydisperisity increases as the percentage of Nova PS 3350 increases. We can see that
all blends, including recycled resin, have similar molecular weight and polydispersity,
which would lead us to predict similar mechanical properties.
5.3.3 Microscopy and Spectroscopy
Fig. 5.5 shows the environmental scanning electron microscope (ESEM) images
of different blends. It is found that for virgin resins, 100% Huntsman PS 702 and Nova
PS 3350, the outer surfaces are dotted with a broad range of rubber domain with many
199
large rubber particles. The diameter is about 2 µm. However, for 50% Huntsman PS 702
and 50% Nova PS 3350, we only observed relatively smaller rubber particles. The
diameter is about 1 µm. The surface structures for the 50% blends are less regular
compared to those of virgin resins. For the PCR, we did not observe well defined rubber
domains, and the surface was seemingly covered with poorly defined dispersed rubberphase and some very small particles which may be contaminants.
Figs. 5.6 and 5.7 show the Raman Spectroscopy and Infrared vibrational spectra
of recycled resin and virgin resin Huntsman PS 702, respectively. It is shown that
recycled resin and virgin resin consist of almost the same components. Combined with
the results of the molecular weight measurements, we predict that it is possible to mix the
recycled resin and virgin resin for potential synergistic improvement of their properties.
5.3.4 Processing Parameters for ASTM Specimens
At first, the geometry was evaluated and then the mesh for the C-COLD
simulation was created. Processing parameters for the ASTM specimens of Huntsman PS
702 from the C-MOLD simulation are given in Table 5.4.
To compare the mechanical properties of the blends of Huntsman PS 702 to the
properties of blends of Nova PS 3350, the same injection molding parameters were used
to prepare the specimens of blends of Nova PS 3350.
5.3.5 Physical Properties of ASTM Specimens
For the six blends of Huntsman PS 702, the minimum, maximum, and average for
the Ra and the Wa are shown in Figs. 5.8 and 5.9 respectively. As shown in the figures,
200
the roughness average was fairly stable for the various blends but the waviness average
was best for the 0% virgin material. Due to our sample size of fifteen data points per
blend, further tests are being conducted with a larger sample size.
For the blends of Huntsman PS 702, the results of the physical properties tested
are shown in Figs. 5.10-5.12. For each physical property, six samples were tested. The
data shown in Figs. 5.10-5.12 are the averages of each sample. Fig. 5.10 shows the
tensile modulus and tensile strength of the blends for two different virgin resins versus
weight percentage of virgin resin. It is found that generally, both the tensile strength and
tensile modulus decrease slightly with the increase of the weight percentage of virgin
resin for the blends with virgin resin Huntsman PS 702, while the tensile strength and
tensile modulus increase slightly with the increase of the weight percentage of virgin
resin for the blends with virgin resin Nova PS 3350. The standard deviation of 12
samples at each percentage was calculated for each physical property. The average of the
standard deviations for the six blends of the tensile strength and the tensile modulus are
0.63 and 67 respectively. Fig. 5.11 illustrates the results of flexural modulus and flexural
strength. It is shown that flexural strength, like the tensile strength for the blends of
Huntsman PS 702, decreases slightly. For the blends of Nova PS 3350, flexural strength
has the same trend as tensile strength and increases slightly. However, flexural modulus
has no specific changing trend for the blends of both Huntsman PS 702 and Nova PS
3350. The average of the standard deviations over the six blends of the flexural strength
and the flexural modulus are 0.60 and 46 respectively.
201
As shown in Fig. 5.12, the impact strength of the blends of Huntsman PS 702
increases with the increase of weight percentage of recycled HIPS when the percentage is
small. At 75% and greater recycled HIPS, the strength reaches a stable value. For impact
strength of the blends of Nova PS 3350, it decreases with the increase of weight
percentage of virgin resin when the percentage is small. At 75% and greater virgin resin,
the strength reaches a stable value. The average of the standard deviation over the six
blends of the impact strength is 2.6.
Though Raman Spectroscopy and Infrared vibrational spectra show that recycled
resin and virgin resin consist of almost the same components, and the blends have similar
molecular weight and polydispersity, ESEM shows that the different blends have very
different microstructure and different rubber domain sizes. Thus, it is not surprising that
the different blends have different mechanical properties because the mechanical
properties of HIPS can be affected by the amount of rubber added, the type of rubber,
rubber size distribution, phase volume, the degree of crosslinking, or the level of adhesion
[Hobbs, 1986; Cook, et al., 1993]. The reason for the higher tensile modulus, tensile
strength, flexural strength, and impact strength of PCR compared to Huntsman PS 702
probably results from the higher tensile modulus and tensile strength of the original
material or the addition of reinforcements in pure resin when the printers and monitors
were made.
Also, the experiments demonstrated that the mechanical properties of
recycled HIPS were slightly lower than those of Nova PS 3350. It is interesting to note
that the mechanical properties of blends with Huntsman PS 702 and recycled resin are
slightly better than the properties of the selected virgin material Huntsman PS 702. Our
202
experiments demonstrate that it is possible to reuse the post-consumer resin. Relative to
the selected virgin materials with the same viscosities as the post-consumer resin, reuse of
the post-consumer resin is an attractive option.
We compared our 100% PCR tensile and flexural properties with those published
in a study comparing disassembled versus shredded HIPS from post-consumer television
sets [Langerak, 1997]. It is found that the tensile modulus of our blends is lower than that
of the disassembled or shredded HIPS in the published study [Langerak, 1997]; however
the tensile strength at yield of our blends is larger. It is also shown that the flexural
modulus of our blend is lower than that of disassembled or shredded HIPS in the other
study [Langerak, 1997], but the flexural strength is almost the same. The differences in
mechanical properties of the PCR in the two studies may result from the different brands
of the original materials.
5.3.6 Application
Before making the real film cans, the injection molding process was simulated by
C-MOLD 97.7. The mesh is shown in Fig. 5.13. The simulation results are listed in
Table 5.5.
Film canisters were made using post-consumer Huntsman HI/PS 702 virgin resin
blends. To obtain initial machine settings, we used the simulation results from C-MOLD
97.7 and IDES's handbook of injection molding specs [IDEAS, 1999].
difference between these resources is the processing temperature.
The main
The handbook
recommended a lower temperature, 221°C, while C-MOLD recommended a higher
203
temperature, 243°C. After experimental trials, we selected the machine settings as shown
in Table 5.5.
The tensile tests for the film canisters were performed on the Instron machine.
The results are listed in Table 5.6. It is shown that the tensile strength of the blends with
Huntsman PS 702 increases with the increase of the weight percentage of recycled resin.
The reason is that Huntsman PS 702 has lower tensile strength than the PCR and thus the
PCR increases the tensile strength of the blend. If the PCR is cheaper and has a higher
tensile strength than a virgin resin with similar rheology, then the PCR can be selected to
increase the mechanical property or properties.
5.4 CONCLUSIONS
To determine the initial processing conditions for injection molding virgin/postconsumer resin blends, a precharacterized resin must be designated for a C-MOLD
simulation. To select a precharacterized resin for the C-MOLD simulation, virgin resin
viscosity curves were matched with the PCR viscosity curve. Then the recommended CMOLD simulation processing parameters were further refined for the blends for the
ASTM test standard specimens by running several experimental runs. In our proposed
approach, we can characterize and represent the PCR in a mold filling simulation by the
virgin resin in the database.
Experimental testing to determine injection molding
parameters for various blends is greatly reduced by this approach.
All blends have similar molecular weight and polydispersity. Furthermore, the
recycled resin and virgin resin consist of almost the same components, as shown in their
204
Raman and infrared spectra. For the ASTM specimens molded with either set of blends,
the mechanical properties are similar. The tensile modulus, tensile strength, and flexural
strength increase slightly with the increase of the weight percentage of PCR for the
blends of Huntsman PS 702. The impact strength increases with the increase of weight
percentage of PCR when the percentage is small and finally the strength reaches a stable
value. It is found that the physical properties of blends having recycled resin are better
than the properties of virgin resin Huntsman PS 702. On the other hand, the mechanical
properties of PCR with Nova PS 3350 are slightly lower when compared to the pure
virgin Nova PS 3350 resin.
205
Materials
Mn
Mw
Polydispersity
100% Huntsman 702
58198
180875
3.06
50% Huntsman 702
56730
171486
3.03
0% Huntsman 702
55262
162099
2.93
100% Nova 3350
54129
196963
3.64
50% Nova 3350
55724
181306
3.26
Virgin Nova 3350
57577
183095
3.18
Table 5.1 Molecular weight (Number average Mn and weight average Mw)
and polydispersity
206
No
1
Weight percentage
Of virgin resin (%)
100
Weight percentage of
Recycled material (%)
0
2
85
15
3
75
25
4
50
50
5
25
75
6
0
100
Table 5.2 Weight percentage blends
207
Description
Film canister
Maximum dimension
49.40 mm
Maximum flow length
65 mm
Volume
560 mm 3
Thickness
0.76 mm
Gate geometry
Rectangular,
0.130 in wide
0.075 in deep
Projected area
730 mm 2
Table 5.3 Mold design characteristics
208
Max machine clamp force
4.90E+007 N
Max machine injection volume
0.02 m3
Max machine injection pressure
1.8E+008 Pa
Max machine injection rate
0.006667 m3/s
Fill time
2.00 s
Post-fill time
12.08 s
Mold-open time
2s
Ambient temperature
298 K
Min/max melt temperature
449.15/533.15 K
Transition temperature
365.15 K
Inlet melt temperature
522.09 K
Average coolant temperature
298 K
Table 5.4 Processing parameters from C-MOLD
209
Resin
Coolant
The maximum flow length
Thickness
Projected area
Volume
Coolant channel diameter
Clamp force
Mold open time
Mold temperature
Min. Processing temperature
Max. Processing temperature
Max. machine inj. Press.
Melt temperature
Fill time
Huntsman HI/PS 702
Pure water
65 mm
0.76 mm
7.3 cm 2
0.56 cm 3
7 mm
50 ton(m)
2s
34.5°C
176°C
260°C
180 MPa
242.9°C
0.49 s
Table 5.5 CMOLD parameters for film canister
210
wt% of virgin resin Tensile strength (MPa)
of Hunstman PS 702
0%
25%
50%
75%
85%
100%
17.54
15.69
16.02
15.42
14.76
14.78
Tensile strength
(MPa) of NOVA PS
3350
17.54
16.31
16.36
17.62
17.91
19.44
Table 5.6 Tensile strength of film canisters
211
Fig. 5.1. Film canister.
212
Viscosity (Pa.s)
1.E+04
1.E+03
PCR
Huntsman PS 702
Nova PS 3350
1.E+02
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
Frequency (1/s)
Fig. 5.2. Comparison of the viscosity curves for post-consumer HIPS
and virgin HIPS at 220°C.
213
Viscosity (Pa.s)
1.E+05
1.E+04
1.E+03
1.E+02
1.E-02
0% at 198.0°C
25% at 197.5°C
50% at 197.6°C
75% at 197.5°C
85% at 197.7°C
100% at 197.4°C
1.E-01
1.E+00
1.E+01
1.E+02
Frequency (1/s)
Fig. 5.3. Viscosity of Huntsman PS 702 blends with different percentages of postconsumer resin at about 200°C.
214
Viscosity (Pa.s)
1.E+05
1.E+04
1.E+03
1.E+02
1.E-02
0% at 198.0 °C
25% at 197.3 °C
50% at 197.5 °C
75% at 197.7 °C
85% at 197.1 °C
100% at 197.7 °C
1.E-01
1.E+00
1.E+01
1.E+02
Frequency (1/s)
Fig. 5.4. Viscosity of Nova PS 3350 blends with different percentages of post-consumer
resin at about 200°C.
215
(a) 100% Huntsman PS 702
(b) 100% Nova PS 702
(c) 50% Huntsman PS 702
(d) 50% Nova PS 702
(e) PCR
Fig. 5.5. The images of different blends from ESEM
(The length of the scales in the figures are 2 µm).
216
Huntsman PS
Fig. 5.6. Raman spectroscopy of injection-molded
post-consumer and Huntsman PS 702.
217
PC
Huntsman PS 702
Fig. 5.7. Infrared vibrational spectra of injection-molded
post-consumer and Huntsman PS 702.
218
0.45
R(a) [micrometers]
0.40
0.35
0.30
0.25
0.20
0.15
0.00
0.25
0.50
0.75
0.85
1.00
Percentage of the virgin material
Fig. 5.8. Average Ra for six blends of Huntsman PS 702.
219
0.40
W(a) [micrometers]
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
0%
25%
50%
75%
85%
100%
Percentage of the virgin material
Fig. 5.9. Average Wa for six blends of Huntsman PS 702.
220
30
2500
2000
20
1500
15
1000
10
Tensile strength of Huntsman PS 702
Tensile strength of Nova PS 3350
5
Tensile mudulus(MPa)
Tensile strength (MPa)
25
500
Tensile modulus of Huntsman PS 702
Tensile modulus of Nova PS 3350
0
0%
20%
40%
60%
80%
0
100%
Weight percentage of virgin resin
Fig. 5.10. Tensile strength and tensile modulus vs. weight percentage of virgin resin.
221
2500
2000
1500
1000
Flexural strength of Huntsman PS 702
Flexural strength of Nova PS 3350
500
Flexural modulus of Huntsman PS 702
Flexural modulus (MPa)
Flexural strength (MPa)
50
45
40
35
30
25
20
15
10
5
0
Flexural modulus of Nova PS 3350
0%
20%
40%
60%
80%
0
100%
Weight percentage of virgin resin
Fig. 5.11. Flexural strength and flexural modulus vs. weight percentage of virgin resin.
222
120
Impact strength (MPa)
100
80
60
40
Huntsman PS 702
20
Nova PS 3350
0
0%
20%
40%
60%
80%
100%
Weight percentage of virgin resin
Fig. 5.12. Impact strength and tensile modulus vs. weight percentage of virgin resin.
223
Fig. 5.13. Meshing model of the film canister.
224
CHAPTER 6
CONCLUSIONS AND RECOMMENDATIONS
6.1 FLOW MARKS
For alternate dull and glossy flow marks, the effect of polymer rheology,
injection speed, mold geometry, melt temperature, mold temperature, holding pressure,
injection pressure, and mold surface coatings on the appearance of the flow marks was
studied. It was found that the most important factor affecting the flow marks was
injection speed.
The flow marks occurred above a critical wall shear stress, but
disappeared at high injection speeds. Mold geometry had an effect on the flow marks,
but mold temperature and melt temperature did not have much effect on the flow marks.
No difference was observed between the crystallinity of dull regions and shiny regions.
However, it was found from Scanning Electron Microscopy that the melt in dull regions
was only slightly oriented while the melt in shiny regions was highly oriented. It was
also found that coating these surfaces did not prevent the occurrence of the flow marks,
although it could alleviate them. It was also found that the polymer with the highest
dynamic viscosity, elastic modulus, first normal stress difference, transient extensional
viscosity, and longest relaxation time exhibited flow marks over a wide range of
processing conditions. Slip was not the cause of the generation of the alternate flow
marks. The generation of the flow marks was explained by an entry viscoelastic flow
instability.
225
Synchronous dull and glossy flow marks were also studied.
The effect of
operating parameters, mold geometry, and mold surface coatings on the flow marks was
investigated. The flow marks occurred above a certain flow front velocity. It was also
found in the experiment that the flow marks were dimmer as the mold temperature was
increased.
No difference was observed between the crystallinity of dull and shiny
regions. However, polymer was highly oriented in shiny region while it was slightly
oriented in dull regions. It was also found that mold surface coatings did not eliminate
the flow marks. Extrusion experiments showed that helical gross melt fracture occurred
for both HDPEs. Finally, it was proposed that an entry viscoelastic instability was the
reason for the generation of the synchronous flow marks.
For the future work, we will prove the mechanism of the entry flow instability.
More evidence is favored for the proposed mechanism. For example, the possible
pressure fluctuation relating to melt fracture (flow marks) will be monitored. Using the
glass window mold in our lab, the flow before the gate and the flow front will be
visualized and recorded by high-speed camcorder. Then the flow will be analyzed.
Moreover, the possibility of slip will be analyzed. The extensional viscosity will be
measured to describe the fountain flow more accurately, and its effect on the formation
of vortices will be analyzed. Furthermore, fundamental mechanism for the formation of
the flow marks will be studied. The detailed morphology, crystallinity and structure of
crystalloids, and the effective thickness of the flow marks will be investigated.
6.2
EXPERIMENTS
WITH
MICRO-FEATURES
AND
SIMULATION
ACCURACY IMPROVEMENT
Thin-wall injection molding with micro-features was studied experimentally and
numerically. The filling lengths in microchannels are affected by injection speed, mold
temperature and channel location. It was found that high injection speed or high mold
temperature results in longer filling length.
226
Moreover, the filling lengths in
microchannels increase with the decrease in the filling time flowing from the
microchannels to the main flow end. Furthermore, the filling lengths in microchannels
are simulated by a hybrid simulation code with a combination of the momentum
equation and the Hele-Shaw model, and compared with experimental results. The code
has fewer elements and requires less computation time. The simulation shows that the
filling lengths in microchannels are sensitive to the heat transfer coefficients in the main
flow cavity and in the microchannel and extra attention is needed to determine proper
heat transfer coefficient. Using the variable heat transfer coefficient, the filling length in
the long mold is predicted accurately.
Our future work will study the thin-wall injection molding of smaller
microchannels with the width of 50 µm and the depth of 250 µm. The morphology of
the microchannels, demolding problem, filling, freezing pattern, repeatability, durability,
and the deformation of the wall of the microchannels will be studied. Moreover, the
filling lengths in microchannels with different main flow thicknesses will be compared
to study which main flow thickness is beneficial to long filling lengths. The argument is
that in the thick mold the melt temperature is high but the pressure drop is low; in the
thin mold the temperature is low but the pressure drop is high. So it is difficult to decide
which mold thickness is favorable to long filling lengths. Furthermore, the filling length
will be measured and it will be compared with simulation results. The effect of heat
transfer coefficients both in the main flow and in the microchannels will be paid full
attention.
For the cavity pressure, the simulation showed that the effect of pressure on the
specific volume is the most important factor to predict the peak cavity pressure. The
effect of pressure on the viscosity and the heat transfer coefficient are also significant.
The heat capacity and the juncture loss are relatively less important compared to other
factors considered here. Therefore, it is very important to use proper material property
227
models when running simulation of thin-wall injection molding. It was also shown that
the significant factors are somewhat different to predict maximum cavity pressure drop.
The effect of the pressure-dependent viscosity, the heat capacity, the heat transfer
coefficient, the juncture pressure loss and the pvT-data on the cavity pressure and
pressure drop were studied. Another important thermal property, thermal conductivity,
would be included for future work. Furthermore, future work could study the effect of
these properties on the filling length in main flow and even in microchannels.
When the injection speed was high, the discrepancy between the simulation
results and experimental data was large and no good agreement could be achieved no
matter what property models were used. So, the reason for the discrepancy might not be
included within the factors we considered. The possible reason may be the difference
between the set operating values and the actual conditions the machine reached. For
example, the actual injection speed is intrinsically slower than the speed one sets,
especially at high injection speeds, as the machine needs response time to reach the
desired constant injection speed. The actual temperature in the barrel may be different
from the set temperature. The effect of these differences should be checked.
Material property measurement and models will affect the simulation results and
proper conclusions. The pressure dependent viscosity was measured under relatively
low pressure and then extrapolated to high pressure. Future work should measure the
viscosity under very high pressure to get a more accurate pressure dependent viscosity
model. The heat capacity was measured at a low heating rate of 3.33ºC/s. It is very
useful to get the “true” value because the cooling rate is very fast in thin-wall injection
processes. The heat transfer coefficient has a large effect on the cavity pressure and the
default value 25,000 W/m2⋅K must be re-evaluated to obtain good simulation results
because other researchers’ work and the current work showed that the default is too
large.
228
Finally, the software itself may affect the final pressure prediction due to its
simplification, such as the assumption of Hele-Shaw flow. Hele-Shaw flow neglects
flow in the gapwise direction and gives the average information in the gapwise direction.
It cannot accurately predict the fluid behavior at the flow front and the flow near or at
solid walls, the phenomenon occurring at the merging of two or more streams (weld
lines), and the kinematics in ribs, gates, or sudden contractions/enlargement. Moldflow
1
is a 2 D software and uses mid-plane mesh. So, developing the code with less
2
assumptions or 3-D mesh based on our group’s previous work may provide more
accurate pressure prediction.
6.3 REUSE OF HIPS
This part focuses on the mechanical and rheological properties of virgin and
recycled high impact polystyrene materials. The study shows that all blends have similar
molecular weight and polydispersity. Furthermore, the recycled resin and virgin resin
consist of almost the same components, as shown in their Raman and infrared spectra.
For the ASTM specimens molded with either set of blends, the mechanical properties are
similar. The tensile modulus, tensile strength, and flexural strength increase slightly
with the increase of the weight percentage of PCR for the blends of Huntsman PS 702.
The impact strength increases with the increase of weight percentage of PCR when the
percentage is small and finally the strength reaches a stable value. It is found that the
physical properties of blends having recycled resin are better than the properties of virgin
resin Huntsman PS 702. On the other hand, the mechanical properties of PCR with
Nova PS 3350 are slightly lower when compared to the pure virgin Nova PS 3350 resin.
Our experiments demonstrate that the PCR may have good material properties and may
even be used in a more challenging application.
229
Moreover, the study introduces a new approach to determine initial processing
parameters for injection molding of post-consumer resin.
To determine the initial
processing conditions for injection molding virgin/post-consumer resin blends, we can
characterize and represent the PCR in a mold filling simulation by the virgin resin in the
database. This approach greatly reduces experimental testing to determine injection
molding parameters for various blends. This approach for plastics recycling is novel
because we started with an initial rheological investigation of PCR characteristics rather
than tracking the original virgin resin. We also tested our new approach by molding the
PCR in a thinner wall design application.
There are several areas of this research requiring more study in future. In our
study, two different virgin resins were identified by PCR characterization.
Both
candidates had similar viscosity versus shear rate curves, but different melt flow indices.
Because plastics have complex properties, further study is needed to identify the
properties of the unknown PCR, and then find virgin resins that match additional
characteristics, such as mechanical properties. Then, the mechanical properties of a
specific design with different percentage of PCR will be predicted. It will further
improve the decision tool to decide the threshold of recycling.
Our study used HIPS from computer and monitor housing. More cases are
needed to get more general conclusions. To investigate the sensitivity of our approach to
grade mixtures is an interesting extension of this work. Because shredding different
plastic parts may generate a reground mixture of HIPS PCR grades, it will be useful to
determine whether the viscosity versus shear rates of the resin grade mixture could be
used to identify a proxy virgin resin.
230
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