MFGT 124
Solid Design in Manufacturing
Product Evaluation for Performance and the
Effects of Variation
Professor Joe Greene
CSU, CHICO
Reference: The Mechanical Process, 3rd Edition, David Ullman,
McGrall Hill New York (2003)
MFGT 124
Copyright 2003 Joseph Greene All Rights Reserved
1
Chap 11: Product Evaluation
• Topics
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–
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–
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–
–
–
Introduction
Importance of Functional Evaluation
Goals of Performance Evaluation
Accuracy, Variation, and Noise
Modeling of Performance Evaluation
Tolerance Analysis, ISO 9000, and Six Sigma
Sensitivity Analysis
Robust Design and Taguchi Methods and Design of Experiments
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2
Summary
• Product evaluation should be focused on comparison with
the engineering requirements and also on the evolution of
the function of the product.
• P-diagrams are useful for identifying and representing the
input signals, control parameters, noises, and outputs.
• Concern must be shown for both the accuracy and
variation of the model.
• ISO 9000 and Six Sigma are essential measurable
techniques for modern manufacturing of products.
• Robust design takes noise into account during
experimental design and establishes parameters that are
less sensitive to noise factors.
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3
Introduction
• Goal of this chapter
– Compare performance of the product to the engineering specifications from the
product design phase.
• Performance can be measured
• Mechanical specs. Component and system testing results.
• Cost specs. Piece cost and cycle time to produce part.
• Quality specs. How often can product meet mechanical, cost, dimensional specs.
• Best practices- Table 11.1 (Extension of Table 4.1)
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–
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–
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Monitoring functional change
Goals and modeling of performance evaluation
Accuracy, variation, and noise
Tolerance and Sensitivity analysis
Robust design
Value engineering and design for cost
Design for manufacturing, assembly, and reliability.
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4
Importance of Functional Evaluation
• Evaluating the performance of the product is essential to
the product being used and being sold.
• Important to track changes made in the function of the
product.
• Important to not add unneeded constraints or functions to
product.
• As product matures, the intended function materializes.
• Product design needs to keep up with any changes to
product or performance tests once released
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5
Goals of Performance Evaluation
• Chap 6 developed engineering requirements based upon
needs of the customer.
– For each requirement a target was set.
– Now evaluate the product relative to the targets.
• Measurable targets with numerical values are preferred versus qualitative
values.
– Evaluation of product performance must support these factors.
• Evaluation must result in numerical measures of product.
• Evaluation should give some indication of which features of the product
design to modify in order to bring target back on spec.
• Evaluation procedures must include the influence of variations due to
manufacturing, aging, and environmental changes.
– P-diagram
• P stands for product or process that has some dependent parameters that
affect the quality of that feature.
– Can also use Fishbone diagram to identify cause and effect.
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6
Goals of Performance Evaluation
• P-diagram
• P stands for product or process that is affected by parameters.
– Physical dimension, material properties, forces from other systems,
forces or motions from system.
– Manufacturing parameters that affect product.
» Temperature, pressure, cycle time, operator, machine type.
• Evaluate system need to assess quality measures.
• Have input signals that affect quality. Fig 11.2
– Other methods include design of experiment. (Later)
Parameters Change values or redesign
Input
Signals
Product or
process
Quality Measures
Targets
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7
Precision, Accuracy, and Significance
• Precision
– Indicates repeatability
• Accuracy
– Signifies how close a measurement is to a true value
• Test Significance
– Measure of the extent to which the information obtained through
the test procedure is a predictor of the performance of the same
material in service.
X X
XX
X
X
X
Precision
X
X X
XX
X
X
Accuracy
Precision and Accuracy
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8
ISO 9000, Six Sigma and Other
Quality Mysteries
Copyright 2003 Joseph Greene All Rights Reserved
9
•
Introduction
Times are changing for quality
– In the 1970’s, almost anything manufactured was accepted and shipped.
•
•
•
•
•
Quality was measured but not well controlled.
Quality problems were passed on to customers.
Designs didn’t change too quickly.
Competition was regional with very little from international.
GM had over 50% of the market share of cars.
– In 1980’s worldwide competition forced higher quality.
• Many improvements were needed to get higher quality at lowest cost.
• Labor costs became large and quality per cost ratio
– In the 1990’s time to market became paramount.
• Quality measurements influenced product manufacturing.
• Downsizing, re-engineering, and people changes to meet growing expectations of
customers.
• Highest quality at lowest cost.
• Quality engineering involves the whole product process from cradle to grave or
design concept to manufacturing products to specifications
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10
Introduction
• ISO Technical Committee was formed in 1979
– To harmonize the increasing international activity in quality
management and quality assurance standards. Subcommittee was
established to determine common terminology.
– It developed ISO 8402: Quality-Vocabulary, which was published
in 1986. (ASQ published ANSI/ASQ A8402-1994: Quality Systems
Terminology.
• While this document is not an adoption of ISO 8402, it does contain many of
the exact terms and definitions contained in ISO 8402.)
• Subcommittee 2 was established to develop quality systems standards--the
result being the ISO 9000 series, published in 1987 (revised 1994).
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11
ISO 9000
• The ISO 9000 series is a set of five individual, but related,
international standards on quality management and quality
assurance.
– ISO 9000 requires documentation for everything in manufacturing
process.
– They are generic, not specific to any particular products.
– They can be used by manufacturing and service industries alike.
– These standards were developed to effectively document the quality
system elements to be implemented in order to maintain an efficient
quality system in your company.
– The ISO 9000 Series standards do not themselves specify the
technology to be used for implementing quality system elements.
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12
ISO 9000 Requires Documentation
• RECORDS REQUIRED BY ISO 9001:2000
Clause
5.6.1
6.2.2 (e)
7.1 (d)
7.2.2
7.3.2
7.3.4
7.3.5
7.3.6
7.3.7
7.4.1
7.5.2 (d)
7.5.3
7.5.4
7.6 (a)
7.6
7.6
8.2.2
8.2.4
8.3
8.5.2
8.5.3
Record required
Management reviews
Education, training, skills and experience
Evidence that the realization processes and resulting product fulfill requirements
Results of the review of requirements relating to the product and actions arising from the review
Design and development inputs
Results of design and development reviews and any necessary actions
Results of design and development verification and any necessary actions
Results of design and development validation and any necessary action
Results of the review of design and development changes and any necessary actions
Results of supplier evaluations and actions arising from the evaluations
As required by the organization to demonstrate the validation of processes where the resulting output
cannot be verified by subsequent monitoring or measurement
The unique identification of the product, where traceability is a requirement
Customer property that is lost, damaged or otherwise found to be unsuitable foruse
Standards used for calibration or verification of measuring equipment where no international or
national measurement standards exist
Validity of previous results when measuring equipment is found not to conform with its requirements
Results of calibration and verification of measuring equipment
Internal audit results
Evidence of product conformity with the acceptance criteria and indication of the authority responsible
for the release of the product
Nature of the product nonconformities and any subsequent actions taken, including concessions
obtained
Results of corrective action
Results of preventive action
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13
ISO 9000
• There are several benefits to implementing this series in
your company.
• For example, it will guide you to build quality into your product or service
and avoid costly after-the-fact inspections, warranty costs, and rework.
• In addition, you may also be able to reduce the number of audits customers
perform on your operation.
• Increasingly, customers are accepting supplier quality system registration
from an accredited third-party assessment based on these standards.
– References
• J. Lahey and R. Launsby, Experimental Design for Injection Molding, Launsby
Publishing, Colorado Springs, CO(1998)
• http://www.asq.org
Copyright 2003 Joseph Greene All Rights Reserved
14
ISO 9000
• ISO 9000 provides the user with guidelines for selection
and use of ISO 9001, 9002, 9003 and 9004.
• ISO 9001, 9002, and 9003 are quality system models for
external quality assurance.
– These three models are actually successive subsets of each other.
– ISO 9001 is the most comprehensive--covering design,
manufacturing, installation, and servicing systems.
– ISO 9002 covers production and installation, and
– ISO 9003 covers only final product inspection and test.
• These three models were developed for use in contractual
situations such as those between a customer and a supplier.
– ISO 9004 provides guidelines for internal use by a producer
developing its own quality system to meet business needs
and take advantage of opportunities.
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15
ISO 9000
• The choice of which model to implement depends on the
scope of your operation.
– For example, if you design your own product or service, you must
consider ISO 9001.
– If you only manufacture (working off someone else's design) you
may wish to consider ISO 9002.
– Finally, if you neither design nor manufacture, you may wish to
consider ISO 9003.
Copyright 2003 Joseph Greene All Rights Reserved
16
• Purpose of ISO is
ISO 9000
• to promote the development of standardization and related world activities
• to facilitate the international exchange of goods and services, and
• to develop cooperation in intellectual, scientific, technological, and economic
activity.
• Introduced in 1987 and adopted in 96 countries.
• American National Standard Institute (ANSI) is the member body
representing the US.
– Standards are designed to be utilized by manufacturing, process, and services
•
•
•
•
•
ISO 9000: A road map for use of other standards in this series
ISO 9001: A model for use when the company must design and produce a product
ISO 9002: A model for use when a company produces a product
ISO 9003: A model for quality assurance in final inspection and testing
ISO 9004: Provides quality management and quality system guidelines for use by a
company in developing and implementing a quality system.
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17
ISO 9001
• ISO 9001: A model for use when the company must design
and produce a product
– Section 4.2.3: Quality Planning
– The supplier shall define and document the requirements for quality
will be met. Quality planning shall be consistent with all other
requirements of a supplier’s quality system and shall be documented in
a format to suit the supplier’s methods of operation….
– The supplier shall give consideration to the following:
» the preparation of quality plans,
» the identification and acquisition of any controls, process,
equipment (including inspection and test equipment) fictures,
resources, and skills that may be needed to achieve the required
quality,
» ensuring the compatibility of the design, the production process,
installation, servicing, inspection and test procedures,
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18
ISO 9004
• Reference: http://www.tc176.org/
– This document introduces the eight quality management principles on which the quality
management system standards of the revised ISO 9000:2000 series are based.
– The principles are derived from the collective experience and knowledge of the
international experts who participate in ISO Technical Committee ISO/TC 176, Quality
management and quality assurance, which is responsible for developing and maintaining
the ISO 9000 standards.
– The eight quality management principles are defined in ISO 9000:2000, Quality
management systems – Fundamentals and vocabulary, and in ISO 9004:2000, Quality
management systems – Guidelines for performance improvements.
• Principle 1 – Customer focus
• Principle 2 – Leadership
• Principle 3 – Involvement of people
• Principle 4 – Process approach
• Principle 5 – System approach to management
• Principle 6 – Continual improvement
• Principle 7 – Factual approach to decision making
• Principle 8 – Mutually beneficial supplier relationships
Copyright 2003 Joseph Greene All Rights Reserved
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ISO
9004
Principle 1 – Customer focus
– Organizations depend on their customers and therefore should understand current and
future customer needs, should meet customer requirements and strive to exceed customer
expectations.
– Key benefits:
– Increased revenue and market share obtained through flexible and fast responses to
market opportunities.
– Increased effectiveness in the use of the organization's resources to enhance
customer satisfaction.
– Improved customer loyalty leading to repeat business.
– Applying the principle of customer focus typically leads to:
• Researching and understanding customer needs and expectation
• Ensuring that the objectives of the organization are linked to customer needs and
expectations.
• Communicating customer needs and expectations throughout the organization.
• Measuring customer satisfaction and acting on the results.
• Systematically managing customer relationships.
• Ensuring a balanced approach between satisfying customers and other interested
parties (such as owners, employees, suppliers, financiers, local communities and
society as a whole).
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20
QS 9000
• QS-9000 is the shorthand name for "Quality System
Requirements QS-9000."
– It is the common supplier quality standard for Chrysler
Corporation, Ford Motor Company, and General Motors
Corporation.
– QS-9000 is based on the 1994 edition of ISO 9001, but it contains
additional requirements that are particular to the automotive
industry.
– These additions are considered automotive "interpretations" by the
ISO community of accreditation bodies and registrars.
– QS-9000 applies to suppliers of production materials, production
and service parts, heat treating, painting and plating and other
finishing services.
– It does not, therefore, apply to all suppliers of the Big Three.
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21
Six Sigma
• Ultimate goal is to ship product with zero defects to the customer.
– Six sigma recognizes that defects that are generated prior to shipping still
represent lost time and materials.
– Six sigma helps stop variation in product quality at the earliest possible point.
• The product and process design phase
• Sigma,, is statistical unit of measure which reflects your process
capability. It is the square root of the variance and similar to the
standard deviation.
• The variance is a measure of the spread of the data or how much
variability exits.
• Minimum sigma is best.
• Six sigma means achieving a desired value plus or minus 3 sigma.
– It represents 99.99966% of the data on a bell shaped curve.
• When six sigma quality is achieved, 99.99966% of the products and
services are defect-free.
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22
Six Sigma
• Six Sigma focuses on variations as the number one enemy
in the battle to obtain a high quality product at a low cost.
• Primary sources of variation are
– Inadequate design margin
– Inadequate process control
– Unstable parts and material
• If manufacturers are to achieve six sigma quality, they must isolate,
control, and continuously reduce variation.
• Experimentation is needed to reduce variation.
– Can choose trial and error, or
– Design of experiments with full factorial or partial factorial designs
• Design of experiments (DOE) is the best way to control a process
and reduce variation.
– Taguchi DOE is very popular and very efficient experimentation method.
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23
Need for Need for Experiments
• Need to establish cause and effect relationships
• Home
– Car repair- Trouble-shooting starting, noise, and braking problems
– Home repair- Electrical and mechanical problems, cooking, etc.
– Gardening and lawn maintenance- watering and pesticide use
• School
– Studying versus grades performance
– Attendance versus grade performance
• Industry
–
–
–
–
Maintenance and trouble-shooting of equipment
Effects of moisture, line rate, operators on productivity and quality
Trouble shooting production problems for incoming Materials
Trouble shooting production problems on Target values for performance or
appearance
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24
Experimental Goals
• Statistical Accuracy
–
–
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Proper selection of the responses to be measured
Determination the number of factors that affect a response
The interactions between the factors
The number of repetitions per run
The form of analysis to be completed
• Cost
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–
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Minimize the cost
Reduce the number of experiments to the minimum
Study the main factors
Thoroughly understand the process under study
Choose the minimum number of experiments
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10 Steps to an Effective Design
1. Recognition and Formulation. With the DOE I will solve
________________
•
The first step is to recognize the problem.
–
–
–
A clear statement of the problem can create a better understanding of what needs to
be done.
It is important that there is a measurable objective, which will produce practical
knowledge.
After the problems and objective are decided upon, a team can be formed. It is
important to put together a diverse team in order to obtain unbiased objectives.
2. Quality characteristics. I want to measure the following:
________________
•
Quality characteristics used to measure an experiments output influence the
number of experiments that need to be carried out.
–
–
–
–
The outputs from these experiments can either be attributed to nature, or variable.
Variable characteristics such as dimensions, and strength, generally provide more
information than attribute characteristics such as good or bad.
Successful experiments should define the measurement process including
understanding of how to make the proper measurements.
The measurement system must be capable, stable, and robust.
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26
10 Steps to an Effective Design
3. Selecting Parameters: I will pick the following parameters with high and low:
1. Parameter = ____________
2. Parameter = ____________
3. Parameter = ____________
4. Parameter = ____________
5. Parameter = ____________
6. Parameter = ____________
7. Parameter = ____________
8. Parameter = ____________
•
Low = _______________
Low = _______________
Low = _______________
Low = _______________
Low = _______________
Low = _______________
Low = _______________
Low = _______________
High = ___________
High = ___________
High = ___________
High = ___________
High = ___________
High = ___________
High = ___________
High = ___________
Useful tools for selecting parameters include,
–
Brainstorming, flowcharts, and cause and effect analysis.
–
If important factors are not included in the experiment, then the results may not be accurate.
–
A screening experiment may be useful in identifying the most important parameters
4. Classifying Factors
–
–
–
After selecting parameters, the next step is to classify them into control, noise, and signal
factors.
Control factors are those that can be controlled by an engineer during the production of a
product.
• Control factors are factors that affect target performance, but don't change. These
include mold dimensions.
Noise factors are those factors that cannot be controlled, are difficult to control, or are too
expensive to control.
• These factors include weather, and operator skill.
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27
10 Steps to an Effective Design
5. Determining Levels (See number 3 above)
– Levels are the value that a factor holds in an experiment.
– The number of levels used depends on the experiment.
– For quantitative parameters two levels are generally used unless
non-linearity is expected.
– For qualitative parameters three or more levels are generally used.
6. Interactions
– Interactions between two design and process parameters exist
when the effect of one parameter of the quality characteristic is
different at different levels of the other parameter.
– It must be determined which factors will be the most useful to
study.
– It may be useful to replace an interaction with an additional factor
and study it in the first phase of the experiment.
Copyright 2003 Joseph Greene All Rights Reserved
28
10 Steps to an Effective Design
7. Orthogonal Array (MFGT 141 use the Taguchi L8 Array)
– Orthogonal arrays are a set of tables of numbers created by
Taguchi that allow the study of a large number of control and
noise factors on the quality characteristic in a minimum number
of trials.
– Put the parameters and levels from number 3 above into the Excel
spreadsheet and create the DOE and the order of experiment run.
8. Conducting Phase- Run the experiment
– Conducting the experiments and recording all of the results is the
next step, which must be taken.
– It is important to minimize the change in noise factors (day and
time of running, operator, humidity, environmental conditions
around experiment) as much as possible during this step.
Copyright 2003 Joseph Greene All Rights Reserved
29
10 Steps to an Effective Design
9. Analysis- (Use the ANOVA software to determine significance of each
parameter, error% of experiment, and best level for each parameter No. 3)
– After conducting the experiments the data must be analyzed.
– Statistical analysis should provide sound and valid conclusions.
•
•
Open the ANOVA.bat file and input the data from the experiment according to:
Perform DOE Analysis with ANOVA.
10. Implementation
– In order to validate experimental conclusions, a confirmatory experiment
should be performed.
– If these results fall inside the range of confidence then they should be
implemented into the process.
•
•
•
Experimental design techniques based on Taguchi can offer improvements in
product quality and cost.
The experimental design methodology advocated by Taguchi emphasizes the
importance of quality in the design stage.
Using this technique helps to develop products and processes that are robust
against sources of variation.
Copyright 2003 Joseph Greene All Rights Reserved
30
Significance of Difference
• Level Averages
– Sum Differences from Table
– Graph Results
• Analysis of Variance
–
–
–
–
–
Statistical Measurement Method
Measures the total variability in the data measured by the Sum of Squares
Separate out the the differences caused by the individual factors
Calculates the differences caused by the error
Uses the F statistic to calculate the significance
Copyright 2003 Joseph Greene All Rights Reserved
31
ANOVA Example
• Analysis of Variance
Source of
Variation
Sum Of
Squares
Degrees of
Freedom
Mean
Square
F statistic
Factor A
SSFactor A
#Levels -1
SS/Df
MSA/MSE
Factor B
SSFactor B
#Levels -1
SS/Df
MSA/MSE
Error
SSError
n-a
SS/Df
Total
SSTotal
Sample size
n-1
SSFactor A = Page 334
SSFactor B = Page 334
SSTotal = Page 334
Note: F Statistic determines
significance. If F is greater than a
specified value than the factor
is significant.
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32
Taguchi Experimental Design
• History of Dr. Genichi Taguchi
– After WWII, the Japanese initiated a major effort to participate in the world
market.
– The first products were inexpensive, but of poor quality.
– The Japanese government set up government agencies modeled after US
companies (Bell Labs). One such company, Electrical Communication
Laboratories of Japan (ECL), hired Dr. Taguchi to reduce the cost of
experimentation.
– Dr. Taguchi developed a series of experiments that resembled partial factorial
designs and featured orthogonal (balanced) arrays.
– The experimental method is called “The Taguchi Approach”
Copyright 2003 Joseph Greene All Rights Reserved
33
Comparison: Taguchi vs. Conventional
Experimental Design
• Traditional experimental designs were introduced by R.A. Fisher in
1920’s in England
• Limitations of traditional design
–
–
–
–
Limited variety of layouts and difficult data analysis
Limited number of variables with many required repetitions
Passive approach to interactions. Difficulty in resolving them
F statistic only recognized as fully significant. Partial effects are not calculated
• Taguchi has
– Multiple layouts and designs and efficient data analysis
– Minimum number of experiments
– Active approach to interactions and calculates partial contribution
Copyright 2003 Joseph Greene All Rights Reserved
34
Features of Taguchi
• Orthogonal Arrays
–
–
–
–
Efficient data collection
Separated effects from one another
Balanced, separable, or not mixed
Minimum number of experiments
• Experimental Designs
– Two Level- L8, L16, L32 have 8 experiments, 16 experiments, and 32
experiments, respectively
– Three Level- L9, L27 have 9 experiments and 27 experiments.
• Data Analysis- Software available
– Level Averages
– ANOVA
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35
Examples Taguchi
• Design of Experiment for thermoplastic composites
• Objectives
– What is the best combination of Twintex composites and GMT?
– What are the optimum process conditions?
• Paper for SAE
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36
Improving Performance of BMC
Bumper Beams
DOE Study
• Evaluate Effectiveness of Prepreg Technology to
Selectively Increase Stiffness & Impact Performance
• Find Optimum Combination of the 2 Materials
• 4 Variables were Compared vs Static Load :
– Prepreg Type
– BMC Glass %
– Weight Fraction of Prepreg
– Tonnage of Press
Static Test Setup with a Pendulum Face
Moving at a Constant Speed into a
Rigidly Mounted Beam
constant
speed
Pendulum Face
F
Bumper Beam
a. Cross Car
Pendulum Face
Bumper Beam
b. Cross Section
DOE Study
• TP-BMC Glass Weight Percentage:
 20%,
 30%, and
 40%.
• .Weight percentage of prepreg:
 25%,
 50%, and
 75%.
• .Press Tonnage (metric):
 450 t,
 675 t, and
 900 t.
• .Prepreg type:
 satin weave (1:1),:
 twill weave (4:1), and
 unidirectional (uni);
Products
Material
Density
(g/cm3)
1.11
Glass
Volume
(%)
13
Tensile
Strength
(MPa)
101
Tensile
Modulus
(GPa)
6
TP-BMC30
TP-BMC40
GMT+
Satin
Twill
Uni
1.19
19
114
7
1.19
1.47
1.47
1.64
19
35
35
50
130
240
400*
675*
6
13
22*
37*
Improving Performance of BMC
Bumper Beams
DOE Study
• Materials Processed on conventional BMC and GMT
Equipment
• BMC logs were extruded. Prepreg Plates Cut to Shape and
heated in GMT oven
• Projected Area of Part was 370 x 1520 mm, with Nominal
Thickness of 8 mm
• GMT & Prepreg added in Combinations of Fractions of
Prepreg to Total Beam Weight
• 3 Beams in each Combination Molded for Experiment
Experimental Layout for the Taguchi L-9
EXPERIMENT
NUMBER
TP-BMC
GLASS %
(wt)
PREPREG
% BY WT.
TONNAGE
(t)
TYPE OF PREPREG
NUMBER OF PARTS
1
2
3
4
5
6
7
8
9
Control 20%
Control 30%
Control 40%
20%
20%
20%
30%
30%
30%
40%
40%
40%
20%
30%
40%
25%
50%
75%
25%
50%
75%
25%
50%
75%
0%
0%
0%
450
650
900
650
900
450
900
450
650
450
450
450
Satin
Uni
Twill
Twill
Satin
Uni
Uni
Twill
Satin
none
none
none
3
3
3
3
3
3
3
3
3
5
5
5
Note: Equivalent Full Factorial Design would require 81 experiments
: Number of Experiments = (levels)Factors = 34 = 81 experiments
Static Load for BMC and Prepreg
Static Load for BMC/ Prepreg Experiment
35
Ave ra g e
30
25
20
15
Expe rime nt Numbe r
Experiment Number
BMC40
BMC30
BMC20
9
8
7
6
5
4
3
2
10
1
Ave ra ge S ta tic Loa d , kN
Sta nd a rd De via tio n
Level Averages for GMT/Prepreg
Dimensionless Load** Level Averages
850
750
700
650
600
550
Variable Level
Uni
Twill
Satin
TonHigh
TonMed
TonLow
Prepreg75
Prepreg50
Prepreg25
BMC40
BMC30
500
BMC20
Dimensionless Load
800
Analysis of Variance(ANOVA) Results
Significance Of Each Variable
Source
TP-BMC Glass
Weight Percentage
Weight Percentage
of Prepreg
Press Tonnage
GMT Type
(metric)
Prepreg Type
e1
e2
Total
Lay-Up
Df
Sum of Squares
Variance
2
6604
3302
2
22065
2
8121
4210
5710
2855
2
2
0
18
26
2
82651
0
4645
4622
47444
F
S'
10.66
rho %
5984
11032 1498535.6319.682144528446
310
2063
13.60
41325
54.28
9.20
12.52
2311
3.04
0
18
0
13704
761
Total
26
150007
5770
81128
18.96 45.20
54.08
5091
9531
e1
e2
7802
12.61
17539
7122
16.44
10.73
11.69
3100
2.07
19795
13.20
100
15.01
100
Optimum Levels of Each Variable as
Determined from Level Averages
Graph
Variable
Optimum Level
TP-BMC Glass Weight Percentage
Weight fraction of prepreg
Press Tonnage (metric)
Prepreg type
TP-BMC with 30 % glass fibers
75% percentage prepreg
900 tons
Satin (1:1)
Beams
Confirmation Run
• Confirmation Run used same Process Settings
• Used the GMT product with 30% Chopped Fiber & Each
of the Prepreg Materials
• 5 Beams with Each Prepreg Material were made, plus 5
Control Beams
• Test Results confirmed C-GMT 30+ Product was
Improved by Adding Prepreg Material
Conclusions
• Comingled thermoplastic prepregs improve the stiffness properties
of TP-BMC composites by 15% to 20%.
• The static load of composite bumper beams increases with up to a
maximum of 22% to 25% glass (by volume).
• Comingled thermoplastic prepregs improve the static bumper
performance of TP-BMC composites to a level superior to
published results for standard GMT materials.
• The significant material and processing parameters in this
experiment are TP-BMC glass weight percentage, weight
percentage prepreg, press tonnage, and prepreg type.
• The optimum levels for maximum dimensionless static load are:




TP-BMC glass weight percentage = 30%
Weight percentage prepreg = 75%
Press tonnage (metric) = 900 t
Prepreg type = Satin