International Journal of Mechanical Engineering and Technology (IJMET)
Volume 10, Issue 04, April 2019, pp. 172-177. Article ID: IJMET_10_04_016
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=4
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication Scopus Indexed
Tran Thi Hong
Nguyen Tat Thanh University, Ho Chi Minh city, Vietnam
Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi *
Thai Nguyen University of Technology, Thai Nguyen city, Vietnam
Le Hong Ky
Vinh Long University of Technology Education, Vietnam
Nguyen Quoc Tuan
Thai Nguyen University, Thai Nguyen city, Vietnam
Hoang Tien Dung
Hanoi University of Industry, Ha Noi city, Vietnam
* Corresponding Author
ABSTRACT
This paper shows a study on the influences of the process parameters of wire cut electrical discharge machining (WEDM) on the surface roughness in machining 90CrSi tool steel. For this investigation, an experiment was designed and performed. In addition, 6 input parameters including the pulse on time, the pulse off time, the cutting voltage, the server voltage, the wire feed and the feed speed were carefully chosen for the work. The effects of these factors on the surface roughness were evaluated by analysing variance. Moreover, a regression equation was proposed for determining the surface roughness.
Key words: WEDM, wire-cut EDM, cutting speed, factorial design, tool steel machining.
Cite this Article Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung,
Vu Ngoc Pi, Le Hong Ky, Nguyen Quoc Tuan and Hoang Tien Dung, Effects of Process
Parameters on Surface Roughness in Wire-Cut Edm Of 9crsi Tool Steel, International
Journal of Mechanical Engineering and Technology, 10(4), 2019, pp. 172-177. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=4
http://www.iaeme.com/IJMET/index.asp 172 editor@iaeme.com

Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky,
Nguyen Quoc Tuan and Hoang Tien Dung
WEDM is a non-traditional machining process generally used to cut difficult-to-machine materials and machine-parts with narrow slots or small-radius inside corners. For this reason, there have been many researches on optimization of the WEDM process to find the optimum input factors.
To determinate the assignments in optimizing WEDM process, the latest technology in this area were presented [1]. The otimimum process parameters in WEDM were investigated with different work-materials and many objectives. Durairaj [2] determined the optimum process parameters for wire cut EDM of Stainless Steel SS304 with the use of the Grey relational theory and Taguchi technique. Ugrasen [3] investigated the influence of process parameters when cutting molybdenum wire in order to get the minimum surface roughness and the maximum volumetric material removal rate. Parameswara and Sarcar [4] calculated the optimum input factors when machining brass. Besides, there have been several studies on determining optimum process parameters in WEDM [5, 6, 7 and 8]. Besides, the investigation of wire cut
EDM process have been conducted with several methods. They were experimenal method [10,
11], Genetic Algorithm method [12] and simulation method [13].
This paper introduces a study on modelling the surface finish in wire cut EDM of 9CrSi tool steel. In this work, the influences of the process parameters including the pulse on time, the pulse off time, the cutting voltage, the gap voltage, the wire feed and the cutting speed on the surface roughness were investigated. In addition, a regression model to determine the surface roughness in Wire-cut EDM tool steel 90CrSi was proposed.
For evaluation of the influence of the WEDM process parameters on the surface roughness, 6 input parameters were carefully selected (Table 1). Besides, a 2-levels ½ factorial experimental design was selected. As a results, a number of 26-1=32 experimental tests will be conducted.
The machines and equipments for the experiments is introduced in Table 2.
After performing the experiments, the surface roughness of the samples was measured.
Table 3 shows the input parameters and the the surface roughness Ra.
Parameter
Cutting voltage
Pulse on time
Pulse off time
Server voltage
Wire feed
Feed speed
Table 1 . Input factors
Code
VM
T on
T off
SV
WF
SPD
Unit Low
3
8
13
25
8
4.5
High
9
12
18
35
12
5.5
Machine and Equipment
Machine
Wire
Work-material
Dielectric fluid
Roughness measurement
Table2 . Machines and equipments
Specifications
Fanuc Robocut α-1 iA (Figure 1)
Brass wire of diameter 0.25 mm (Taiwan)
90CrSi; cross section of 22x22 mm 2
Deionised water
Mitutoyo 178-923-2A, SJ-201 (Japan) http://www.iaeme.com/IJMET/index.asp 173 editor@iaeme.com

Effects of Process Parameters on Surface Roughness in Wire-Cut Edm Of 9crsi Tool Steel
Figure. 1 .
Wire-cut EDM machine
Figure 2 presents a graph of the main effect of input factor in order to explore the effects of the input parameters on the surfacce roughness. From this graph it is found that the surface roughness depends considerably on the pulse on time Ton, the cutting voltage VM and the serve voltage SV, in descending order. In addition, it is effected by the pulse off time Toff, the the wire feed WF and the feed speed SPD.
Table 3.
Experimental plans and output response
StdOrder
30
RunOrder
1
CenterPt
1
Blocks VM Ton Toff SV WF SPD
1 9
Ra
(µm)
8 18 35 12 4.5 2.949
4
20
2
3
1
1
1
1
9
9
12
12
13
13
25
25
8
12
4.5
5.5
3.770
3.692
19
1
3
…
28
8
4
5
6
31
32
1
1
1
1
1
1
1
1
1
1
3
3
12
8
13
13
25
25
12
8
4.5
4.5
3.899
3.491
3 12 13 25 8 5.5 3.978
9 12 13 35 12 4.5 3.580
9 12 18 25 8 5.5 3.564
The Pareto chart of the standardized effects is presented in Figure 3. From this figure, the bars which describe the pulse on time (factor B), the server voltage (factor D), the cutting voltage (factor A) and the pulse off time (factor C cross the reference line. Therefore, these factors are statistically significant at the 0.05 level with the response model.
Figure 4 shows the Normal Plot to judge the influence of the input factors on the response.
It is learned from the plot that the server voltage (factor D), the cutting voltage (factor A), the pulse off time (factor C) and the pulse on time (factor B) are the significant effected parameters.
Moreover, the pulse on time (factor B) has a positive standardized effect. The surface roughness increases if its value growths. Besides, the server voltage (factor D), cutting voltage (factor A), the pulse off time (factor C) have negative effects. The surface roughness decreses when their values reduce. http://www.iaeme.com/IJMET/index.asp 174 editor@iaeme.com

Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky,
Nguyen Quoc Tuan and Hoang Tien Dung
Figure. 2.
Main effects plot for surface roughness
Figure.3.
Pareto Chart of the Standardized Effects
Figure. 4. Normal Plot for R a http://www.iaeme.com/IJMET/index.asp 175 editor@iaeme.com

Effects of Process Parameters on Surface Roughness in Wire-Cut Edm Of 9crsi Tool Steel
Figure. 5.
Estimated Effects and Coefficients for R a
Figure 5 describes the estimated effects and coefficients for the surface roughness after ignoring insignificant effects. From the figure, the cutting voltage, the pulse on time, the pulse off time and the server voltage are parameters which have P-values lower than the significance level (0.05) are statistically significant. As a results, the surface roughness can be found by the following equation:
R a
 
VM

0.13429

T on

0.01681

T off

0.01826

SV (1)
In this paper, a study on the influences of the input parameters on the surface roughness in
Wire-cut EDM tool steel 90CrSi was performed. The effectsof several input factors including the server voltage, the cutting voltage, the pulse on time, the pulse off time, the wire feed and the feed speed on the surface roughness were investigated. It can be learned from the study results that the cutting voltage, the pulse on time, the pulse off time and the server voltage are significant effected parameters on the surface roughness. In addition, a regression equation to calculate the surface roughness was proposed.
The work described in this paper was supported by Thai Nguyen University of Technology for a scientific project.
[1] Yushi Takayama, Yushinori Makino, Yan Niu, Hiroyuki Uchida, The Latest Technology of
Wire-cut EDM, Procedia CIRP, Volume 42, 2016, Pages 623-626
[2] G. Ugrasen, H.V. Ravindra, G.V. Naveen Prakash, R. Keshavamurthy, Process
Optimization and Estimation of Machining Performances Using Artificial Neural Network in Wire EDM, Procedia Materials Science, Volume 6, 2014, Pages 1752-1760.
[3] M. Durairaj, D. Sudharsun, N. Swamynathan, Analysis of Process Parameters in Wire EDM with Stainless Steel Using Single Objective Taguchi Method and Multi Objective Grey
Relational Grade, Procedia Engineering, Volume 64, 2013, Pages 868-877.
[4] Parameswara Rao, M Sarcar, Evaluation of optimal parameters for machining brass with wire cut EDM, Journal of Scientific & Industrial Research, Vol. 68, January 2009, pp. 32-
34.
[5] R. Ramakrishnan, L. Karunamoorthy, Modeling and multi-response optimization of Inconel
718 on machining of CNC WEDM process, Journal of Materials Processing Technology,
Volume 207, Issues 1-3, 16 October 2008, Pages 343-349. http://www.iaeme.com/IJMET/index.asp 176 editor@iaeme.com

Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky,
Nguyen Quoc Tuan and Hoang Tien Dung
[6] S. Sarkar, S. Mitra, B. Bhattacharyya, Parametric analysis and optimization of wire electrical discharge machining of γ-titanium aluminide alloy, Journal of Materials
Processing Technology, Volume 159, Issue 3, 10 February 2005, Pages 286-294.
[7] Jin Yuan, Kesheng Wang, Tao Yu, Minglun Fang, Reliable multi-objective optimization of high-speed WEDM process based on Gaussian process regression, International Journal of
Machine Tools and Manufacture, Volume 48, Issue 1, January 2008, Pages 47-60.
[8] Y. S. Tarng, S. C. Ma, L. K. Chung, Determination of optimal cutting parameters in wire electrical discharge machining, International Journal of Machine Tools and Manufacture,
Volume 35, Issue 12, December 1995, Pages 1693-1701.
[9] Basil Kuriachen, Josephkunju Paul, Jose Mathew, Modeling of Wire Electrical Discharge
Machining Parameters Using Titanium Alloy (Ti-6AL-4V), International Journal of
Emerging Technology and Advanced Engineering, Volume 2, Issue 4, April 2012
[10] Anurag Joshi, Wire cut edm process limitations for tool and die steel, International Journal of Technical Research and Applications, Volume 2, Special Issue 1 (July-Aug 2014), PP.
65-68.
[11] M. Panner Selvam, P. Ranjith Kumar, Optimization Kerf Width and Surface Roughness in
Wirecut Electrical Discharge Machining Using Brass Wire, Mechanics and Mechanical
Engineering, Vol. 21, No. 1 (2017) 37–55.
[12] F. Klocke, D. Welling, A. Klink, D. Veselovac, R. Perez, Evaluation of Advanced Wire-
EDM Capabilities for the Manufacture of Fir Tree Slots in Inconel 718, Procedia CIRP,
Volume 14, 2014, Pages 430-435.D. Amrish Raj, T. Senthilvelan, Empirical Modelling and
Optimization of Process Parameters of machining.
[13] Titanium alloy by Wire-EDM using RSM, Materials Today: Proceedings, Volume 2, Issues
4–5, 2015, Pages 1682-1690. http://www.iaeme.com/IJMET/index.asp 177 editor@iaeme.com