Sensitivity analysis of parameters affecting cutting speed and dimensional deviation of wire electrical discharge machining

Document Type : Original Article

Authors

1 Department of Mechanical Engineering, Faculty of Engineering, Arak University, Arak, Iran

2 Department of mechanical engineering, Faculty of Engineering, Arak University, Arak, Iran

Abstract
Wire electric discharge machining is one of the newest, most popular and most accurate non-traditional machining processes, which is being studied. The advantages of this process include precision machining of parts with different hardness or complex shapes. Due to the increasing applications of this type of machining and since increasing the cutting speed and reducing the dimensional deviation in this process are very important, the selection of optimal cutting parameters has an important role to achieve high cutting speed and low dimensional deviation. Improper selection of parameters leads to limitations in output parameters and ultimately reduces productivity; Therefore, in this study, using Sobol statistical sensitivity analysis method, which has the advantage of high accuracy over other methods and extracting a small amount of parameter effect, to investigate the effect of various input parameters, including pulse-on time, pulse-off time, servo gap voltage, peak current and wire tension on the two output parameters of cutting speed and dimensional deviation are discussed. The results obtained from the sensitivity analysis of the expression are that the parameters of the pulse off time and pulse on time are the most effective parameters on the cutting speed with 39% and 37%, respectively, and the servo gap voltage parameters and the pulse on time are the most effective parameters on the dimensional deviation with 59% and 31%, respectively.

Keywords


[1] Jain VK. Advanced machining processes: Allied publishers, 2009.
[2] Dauw DF, Beltrami I. High-Precision Wire-EDM by Online Wire Positioning Control. CIRP Annals. 1994;43:193-7.
[3] Rao RV, Pawar PJ. Modelling and optimization of process parameters of wire electrical discharge machining. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 2009;223:1431-40.
[4] Banerjee S, Prasad BVSSS, Mishra PK. A simple model to estimate the thermal loads on an EDM wire electrode. Journal of Materials Processing Technology. 1993;39:305-17.
[5] Ramakrishnan R, Karunamoorthy L. Multi response optimization of wire EDM operations using robust design of experiments. The International Journal of Advanced Manufacturing Technology. 2006;29:105-12.
[6] Erden A, Bilgin S. Role of Impurities in Electric Discharge Machining.  Proceedings of the Twenty-First International Machine Tool Design and Research Conference: Springer; 1981. p. 345-50.
[7] Jeswani ML. Effect of the addition of graphite powder to kerosene used as the dielectric fluid in electrical discharge machining. Wear. 1981;70:133-9.
[8] Spedding TA, Wang ZQ. Parametric optimization and surface characterization of wire electrical discharge machining process. Precision Engineering. 1997;20:5-15.
[9] Sarkar S, Mitra S, Bhattacharyya B. Parametric analysis and optimization of wire electrical discharge machining of γ-titanium aluminide alloy. Journal of Materials Processing Technology. 2005;159:286-94.
[10] Sanchez JA, Rodil JL, Herrero A, de Lacalle LNL, Lamikiz A. On the influence of cutting speed limitation on the accuracy of wire-EDM corner-cutting. Journal of Materials Processing Technology. 2007;182:574-9.
[11] Muniappan A, Jayakumar V, Ajithkumar R, Veerabhadra SK, Prasanna R. Optimization of WEDM Process Parameters for Cutting Speed using Taguchi technique. Materials Today: Proceedings. 2019;18:332-41.
[12] Puri AB, Bhattacharyya B. An analysis and optimisation of the geometrical inaccuracy due to wire lag phenomenon in WEDM. International Journal of Machine Tools and Manufacture. 2003;43:151-9.
[13] Sharma N, Khanna R, Gupta RD, Sharma R. Modeling and multiresponse optimization on WEDM for HSLA by RSM. The International Journal of Advanced Manufacturing Technology. 2013;67:2269-81.
[14] Saha P, Singha A, Pal SK, Saha P. Soft computing models based prediction of cutting speed and surface roughness in wire electro-discharge machining of tungsten carbide cobalt composite. The International Journal of Advanced Manufacturing Technology. 2008;39:74-84.
[15] Rao C, Sarcar M. Evaluation of optimal parameters for machining brass with wire cut EDM. 2009.
[16] Azam M, Jahanzaib M, Abbasi JA, Wasim A. Modeling of cutting speed (CS) for HSLA steel in wire electrical discharge machining (WEDM) using moly wire. Journal of the Chinese Institute of Engineers. 2016;39:802-8.
[17] Tahmasbi V, Ghoreishi M, Taheri MJMME. Sensitivity analysis of material removal rate in dry electro-discharge machining process. 2016;15:382-6.
[18] Saltelli A, Chan K, Scott E. Wiley series in probability and statistics, in sensitivity Analysis. Wiley New York; 2000.
[19] Cukier R, Levine H, Shuler KJJocp. Nonlinear sensitivity analysis of multiparameter model systems. 1978;26:1-42.
[20] Saltelli A, Tarantola S, Chan KPS. A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output. Technometrics. 1999;41:39-56.
[21] Taheri MJMME. Investigation and sensitivity analysis of dimensional parameters and velocity in the 3D nanomanipulation dynamics of carbon nanotubes using statistical Sobol method. 2019;19:125-35.
[22] Taheri M, Tahmasbi V. The effect of various parameters on material removal rate in brass drilling operations using statistical sensitivity analysis. 2016.
[23] Korayem M, Rastegar ZJIJoN, Nanotechnology. Application of nano-contact mechanics models in manipulation of biological nano-particle: FE simulation. 2012;8:35-50.
Volume 2, Issue 3 - Serial Number 5
Autumn 2022
Pages 310-327

  • Receive Date 14 August 2022
  • Revise Date 31 October 2022
  • Accept Date 21 December 2022