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International Journal of Mechanical Engineering and Technology (IJMET)
Volume 10, Issue 03, March 2019, pp. 644-649. Article ID: IJMET_10_03_067
Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3
ISSN Print: 0976-6340 and ISSN Online: 0976-6359
© IAEME Publication Scopus Indexed
EFFECTS OF PROCESS PARAMETERS ON
CUTTING SPEED IN WIRE-CUT EDM OF 9CRSI
TOOL STEEL
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
Nguyen Thi Hoa
Ministry of National Defence - The Vocational College - No.1
*Corresponding Author.
ABSTRACT
This article presents a study on the investigation of the effects of the input
parameters on the cutting speed in machining 90CrSi tool steel using wire cut electrical
discharge machining (EDM). In this work, experiments were performed with factorial
design with a total of 32 experimental runs. In addition, the input factors including the
pulse on time, the pulse off time, the cutting voltage, the server voltage, the wire feed
and the feed speed were carefully selected for the investigation. The effects of this
factors on the cutting speed were learned by analysing variance. Moreover, a
regression equation to determine the cutting speed was introduced.
Keywords: WEDM, 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 Nguyen Thi Hoa, Effects of Process
Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel, International
Journal of Mechanical Engineering and Technology, 10(3), 2019, pp. 644-649.
http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3
Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel
http://www.iaeme.com/IJMET/index.asp 645 editor@iaeme.com
1. INTRODUCTION
Wire electrical discharge machining (WEDM) is one of the most useful methods for machining
difficult-to-machine materials. As a results, there have been many studies on optimization of
WEDM process to find the optimum process factors.
To review the works in optimization of WEDM process, Yushi Takayama [1] introduced
the latest technology in this area. G. Ugrasen [2] conducted an optimization study on the
influence of process parameters on the accuracy, the cutting speedand the volumetric material
removal rate in WEDM with molybdenum wire. Besides, M. Durairaj [3] presented an
optimization study on calculation of optimum input factors for wire cut EDM of Stainless Steel
SS304. In addition, Parameswara Rao [4] proposed optimum input parameters for WEDM
brass. There have also been many studies on finding optimum process parameters [5, 6, 7 and
8]. Moreover, many methods have been used to calculate the optimum process parameters.
They are simulation method [10], Genetic Algorithm method [11] and experimenal method [12,
13].
This paper presents a study on modelling cutting speed in wire cut EDM of 9CrSi tool steel.
In this study, the effect of the input factors including the cutting voltage, the pulse on time, the
pulse off time, the gap voltage, the wire feed and the cutting speed on the cutting speed were
estimated. Aslo, a regression equation for calculation of the cutting speed when WEDM tool
steel 90CrSi was suggested.
2. EXPERIMENTAL WORK
For evaluation of the influence of the input factors on the cutting speed, 6 process parameters
were carefully chosen (Table 1). In addition, a 2-levels ½ factorial experimental design was
chosen and as a result a number of 26-1
=32 experimental tests will be conducted. Table 2 shows
the machine sand equipments used in the experiment.
Table 1 Input factors
Parameter Code Unit Low High
Cutting voltage VM 3 9
Pulse on time Ton 8 12
Pulse off time Toff 13 18
Server voltage SV 25 35
Wire feed WF 8 12
Feed speed SPD 4.5 5.5
Table 2 Machines and equipments
Machine and Equipment Specifications
Machine Fanuc Robocut α-1 iA (Figure 1)
Wire Brass wire of diameter 0.25 mm (Taiwan)
Work-material 90CrSi, cross section of 22x22 mm2
Dielectric fluid Deionised water
Roughness measurement Mitutoyo 178-923-2A, SJ-201 (Japan)
Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky,
Nguyen Quoc Tuan and Nguyen Thi Hoa
http://www.iaeme.com/IJMET/index.asp 646 editor@iaeme.com
Figure 1 Wire-cut electrical discharge machine
After conducting the cutting tests, the cutting speed was collected. The input parameters
and the output response results (the cutting speed CS) are given in Table 3.
3. RESULTS AND DISCUSSIONS
Figure 2 describes the influence of the main effect of each factoron the cutting speed CS. It is
observed that with the increase of the cutting voltage and the pulse on time the cutting speed
growths considerably. Also, it is effected by the pulse off time Toff, the serve voltage SV and
the wire feed WF. Besides, the cutting speed is not affected by the feed speed SPD.
Table 3 Experimental plans and output response
StdOrder RunOrder CenterPt Blocks VM Ton Toff SV WF SPD
CS
(mm/min)
30 1 1 1 9 8 18 35 12 4.5 1.883
4 2 1 1 9 12 13 25 8 4.5 2.204
20 3 1 1 9 12 13 25 12 5.5 2.212
19 4 1 1 3 12 13 25 12 4.5 1.849
1 5 1 1 3 8 13 25 8 4.5 1.250
3 6 1 1 3 12 13 25 8 5.5 1.732
28 31 1 1 9 12 13 35 12 4.5 2.132
8 32 1 1 9 12 18 25 8 5.5 2.353
Figure 3 presents the trend of the influences of the input factors on the response. From the
figure, it is clear that the pulse on time (factor B) and the cutting voltage (factor A), the pulse
off time (factor C), the server voltage (factor D) and the interactions AC and DF are the
significant effects factors. Moreover, all of them have a positive standardized effect. That means
the cutting speed increases if their values growth.
The Pareto chart of the standardized effects is shown in Figure 4. From the figure, the bars
which symbolyze the pulse on time (factor B), the cutting voltage (factor A), the pulse off time
(factor C), the server voltage (factor D) and the interactions AD and DF cross the reference line.
As a results, these factors are statistically significant at the 0.05 level with the response model.
Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel
http://www.iaeme.com/IJMET/index.asp 647 editor@iaeme.com
Figure 2 Main effects plot for cutting speed
Figure 3 Normal Plot for CS
Figure 4 Pareto Chart of the Standardized Effects
Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky,
Nguyen Quoc Tuan and Nguyen Thi Hoa
http://www.iaeme.com/IJMET/index.asp 648 editor@iaeme.com
Figure 5 Estimated Effects and Coefficients for aR
Figure 5 presents the estimated effects and coefficients for the cutting speed after ignoring
insignificant effects. It is found from this figure that parameters which have a significant effect
on a response have P-values lower than 0.05 are the cutting voltage, the pulse on time, the pulse
off time, the server voltage, the feed speed and the interactions AC and DF. Hence, the cutting
speed is calculated by the following model:
2.09 0.0146 0.13527 0.0023 0.0688 0.503
0.00596 0.01689
on off
off
CS VM T T SV SPD
VM T SV SPD
= −  +  +  +  −  +
+   +  
(1)
4. CONCLUSION
A study on investigation of the effects of the input factors on the cutting speed in wire electrical
discharge machining tool steel 90CrSi was carried out. The influences of many process factors
including the cutting voltage, the server voltage, the pulse on time, the pulse off time, the wire
feed and the feed speed on the cutting speed were inspected. It was found that the cutting
voltage, the pulse on time, the pulse off time, the server voltage, the feed speed and the
interactions AC and DF are significant effected factors on the cutting speed. Also, a regression
model for determining the cutting speed was suggested.
ACKNOWLEDGEMENT
The work described in this paper was supported by Thai Nguyen University of Technology for
a scientific project.
REFERENCES
[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.
Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel
http://www.iaeme.com/IJMET/index.asp 649 editor@iaeme.com
[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.
[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.

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EFFECTS OF PROCESS PARAMETERS ON CUTTING SPEED IN WIRE-CUT EDM OF 9CRSI TOOL STEEL

  • 1. http://www.iaeme.com/IJMET/index.asp 644 editor@iaeme.com International Journal of Mechanical Engineering and Technology (IJMET) Volume 10, Issue 03, March 2019, pp. 644-649. Article ID: IJMET_10_03_067 Available online at http://www.iaeme.com/ijmet/issues.asp?JType=IJMET&VType=10&IType=3 ISSN Print: 0976-6340 and ISSN Online: 0976-6359 © IAEME Publication Scopus Indexed EFFECTS OF PROCESS PARAMETERS ON CUTTING SPEED IN WIRE-CUT EDM OF 9CRSI TOOL STEEL 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 Nguyen Thi Hoa Ministry of National Defence - The Vocational College - No.1 *Corresponding Author. ABSTRACT This article presents a study on the investigation of the effects of the input parameters on the cutting speed in machining 90CrSi tool steel using wire cut electrical discharge machining (EDM). In this work, experiments were performed with factorial design with a total of 32 experimental runs. In addition, the input factors including the pulse on time, the pulse off time, the cutting voltage, the server voltage, the wire feed and the feed speed were carefully selected for the investigation. The effects of this factors on the cutting speed were learned by analysing variance. Moreover, a regression equation to determine the cutting speed was introduced. Keywords: WEDM, 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 Nguyen Thi Hoa, Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel, International Journal of Mechanical Engineering and Technology, 10(3), 2019, pp. 644-649. http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=10&IType=3
  • 2. Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel http://www.iaeme.com/IJMET/index.asp 645 editor@iaeme.com 1. INTRODUCTION Wire electrical discharge machining (WEDM) is one of the most useful methods for machining difficult-to-machine materials. As a results, there have been many studies on optimization of WEDM process to find the optimum process factors. To review the works in optimization of WEDM process, Yushi Takayama [1] introduced the latest technology in this area. G. Ugrasen [2] conducted an optimization study on the influence of process parameters on the accuracy, the cutting speedand the volumetric material removal rate in WEDM with molybdenum wire. Besides, M. Durairaj [3] presented an optimization study on calculation of optimum input factors for wire cut EDM of Stainless Steel SS304. In addition, Parameswara Rao [4] proposed optimum input parameters for WEDM brass. There have also been many studies on finding optimum process parameters [5, 6, 7 and 8]. Moreover, many methods have been used to calculate the optimum process parameters. They are simulation method [10], Genetic Algorithm method [11] and experimenal method [12, 13]. This paper presents a study on modelling cutting speed in wire cut EDM of 9CrSi tool steel. In this study, the effect of the input factors including the cutting voltage, the pulse on time, the pulse off time, the gap voltage, the wire feed and the cutting speed on the cutting speed were estimated. Aslo, a regression equation for calculation of the cutting speed when WEDM tool steel 90CrSi was suggested. 2. EXPERIMENTAL WORK For evaluation of the influence of the input factors on the cutting speed, 6 process parameters were carefully chosen (Table 1). In addition, a 2-levels ½ factorial experimental design was chosen and as a result a number of 26-1 =32 experimental tests will be conducted. Table 2 shows the machine sand equipments used in the experiment. Table 1 Input factors Parameter Code Unit Low High Cutting voltage VM 3 9 Pulse on time Ton 8 12 Pulse off time Toff 13 18 Server voltage SV 25 35 Wire feed WF 8 12 Feed speed SPD 4.5 5.5 Table 2 Machines and equipments Machine and Equipment Specifications Machine Fanuc Robocut α-1 iA (Figure 1) Wire Brass wire of diameter 0.25 mm (Taiwan) Work-material 90CrSi, cross section of 22x22 mm2 Dielectric fluid Deionised water Roughness measurement Mitutoyo 178-923-2A, SJ-201 (Japan)
  • 3. Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky, Nguyen Quoc Tuan and Nguyen Thi Hoa http://www.iaeme.com/IJMET/index.asp 646 editor@iaeme.com Figure 1 Wire-cut electrical discharge machine After conducting the cutting tests, the cutting speed was collected. The input parameters and the output response results (the cutting speed CS) are given in Table 3. 3. RESULTS AND DISCUSSIONS Figure 2 describes the influence of the main effect of each factoron the cutting speed CS. It is observed that with the increase of the cutting voltage and the pulse on time the cutting speed growths considerably. Also, it is effected by the pulse off time Toff, the serve voltage SV and the wire feed WF. Besides, the cutting speed is not affected by the feed speed SPD. Table 3 Experimental plans and output response StdOrder RunOrder CenterPt Blocks VM Ton Toff SV WF SPD CS (mm/min) 30 1 1 1 9 8 18 35 12 4.5 1.883 4 2 1 1 9 12 13 25 8 4.5 2.204 20 3 1 1 9 12 13 25 12 5.5 2.212 19 4 1 1 3 12 13 25 12 4.5 1.849 1 5 1 1 3 8 13 25 8 4.5 1.250 3 6 1 1 3 12 13 25 8 5.5 1.732 28 31 1 1 9 12 13 35 12 4.5 2.132 8 32 1 1 9 12 18 25 8 5.5 2.353 Figure 3 presents the trend of the influences of the input factors on the response. From the figure, it is clear that the pulse on time (factor B) and the cutting voltage (factor A), the pulse off time (factor C), the server voltage (factor D) and the interactions AC and DF are the significant effects factors. Moreover, all of them have a positive standardized effect. That means the cutting speed increases if their values growth. The Pareto chart of the standardized effects is shown in Figure 4. From the figure, the bars which symbolyze the pulse on time (factor B), the cutting voltage (factor A), the pulse off time (factor C), the server voltage (factor D) and the interactions AD and DF cross the reference line. As a results, these factors are statistically significant at the 0.05 level with the response model.
  • 4. Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel http://www.iaeme.com/IJMET/index.asp 647 editor@iaeme.com Figure 2 Main effects plot for cutting speed Figure 3 Normal Plot for CS Figure 4 Pareto Chart of the Standardized Effects
  • 5. Tran Thi Hong, Do Thi Tam, Nguyen Manh Cuong, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky, Nguyen Quoc Tuan and Nguyen Thi Hoa http://www.iaeme.com/IJMET/index.asp 648 editor@iaeme.com Figure 5 Estimated Effects and Coefficients for aR Figure 5 presents the estimated effects and coefficients for the cutting speed after ignoring insignificant effects. It is found from this figure that parameters which have a significant effect on a response have P-values lower than 0.05 are the cutting voltage, the pulse on time, the pulse off time, the server voltage, the feed speed and the interactions AC and DF. Hence, the cutting speed is calculated by the following model: 2.09 0.0146 0.13527 0.0023 0.0688 0.503 0.00596 0.01689 on off off CS VM T T SV SPD VM T SV SPD = −  +  +  +  −  + +   +   (1) 4. CONCLUSION A study on investigation of the effects of the input factors on the cutting speed in wire electrical discharge machining tool steel 90CrSi was carried out. The influences of many process factors including the cutting voltage, the server voltage, the pulse on time, the pulse off time, the wire feed and the feed speed on the cutting speed were inspected. It was found that the cutting voltage, the pulse on time, the pulse off time, the server voltage, the feed speed and the interactions AC and DF are significant effected factors on the cutting speed. Also, a regression model for determining the cutting speed was suggested. ACKNOWLEDGEMENT The work described in this paper was supported by Thai Nguyen University of Technology for a scientific project. REFERENCES [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.
  • 6. Effects of Process Parameters on Cutting Speed in Wire-Cut EDM of 9crsi Tool Steel http://www.iaeme.com/IJMET/index.asp 649 editor@iaeme.com [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. [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.