Mechanic of Advanced and Smart Materials
Quarterly

Analysis of the sensitivity of the parameters affecting the rate of removal, surface roughness and width in the wire electrical discharge machining

Document Type : Original Article

Authors

siavash fathollahi dehkordi 1
Fardin Shabani 2

1 Assistants professor, Mechanic Engineering Department, Shahid Chamran University of Ahwaz, Ahwaz, Khuzestan, Iran

2 University student

https://doi.org/10.52547/masm.2.2.202
Abstract
One of the most attractive modern machining methods is electrical discharge machining, which was introduced in the late 1960s. Electric discharge machining with wires has a number of uses, including high accuracy machining of all conductive materials such as metals, metal alloys, graphite, and ceramics, as well as aerospace, automotive, and other industries. In order to increase the rate and reduce surface roughness and gap width, optimal cutting parameters play a crucial role in selecting output parameters. In this study, input parameters (discharge, pulse duration, pulse frequency, wire speed, wire tension, and dielectric current velocity) were compared to output variables (cutting rate, surface filter, and width). The sensitivity analysis shows that pulse duration parameters, wire speed, and discharge flow are most effective parameters for cutting rate, and pulse duration parameters, dielectric rate, and discharge flow are most effective parameters for surface roughness, as well as pulse duration, wire speed, and discharge current for gap width. Pulse duration with 72%, wire speed with 14%, and discharge current with 10% has the greatest impact on the chip removal rate.

Keywords

Wire Electrical Discharge Machining
Material Removal Rate
Roughness Surface
The width of the gap
Sensitivity analysis
[1] Groover M P. Fundamentals of modern manufacturing: materials, processes, and systems. John Wiley & Sons. 2020.
[2] Kuriakose S, Shunmugam M S. Characteristics of wire-electro discharge machined Ti6Al4V surface. Materials Letters. 2004;58:2231-2237.
[3] Puri A B, 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;43:151-159.
[4] Singh H, Garg R. Effects of process parameters on material removal rate in WEDM. Journal of achievements in materials and manufacturing engineering. 2009;32:70-74.
[5] Puertas I, Luis C J. A study on the machining parameters optimisation of electrical discharge machining. Journal of materials processing technology. 2003;143:521-526.
[6] Mahapatra S S, Patnaik A. Parametric optimization of wire electrical discharge machining (WEDM) process using Taguchi method. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 2006;28:422-429.
[7] Scott D, Boyina S, Rajurkar K P. Analysis and optimization of parameter combinations in wire electrical discharge machining. The International Journal of Production Research. 1991;29:2189-2207.
[8] Rajurkar K P, Wang W M. Thermal modeling and on-line monitoring of wire-EDM. Journal of materials processing technology. 1993;38:417-430.
[9] Tosun N, Cogun C. An investigation on wire wear in WEDM. Journal of materials processing technology. 2003;134:273-278.
[10] Shah A, Mufti N A, Rakwal D, Bamberg E. Material removal rate, kerf, and surface roughness of tungsten carbide machined with wire electrical discharge machining. Journal of materials engineering and performance. 2011;20:71-76.
[11] Liao Y S, Huang J T, Su H C. A study on the machining-parameters optimization of wire electrical discharge machining. Journal of materials processing technology. 1997;71:487-493.
[12] Datta S, Mahapatra S. Modeling, simulation and parametric optimization of wire EDM process using response surface methodology coupled with grey-Taguchi technique. International Journal of Engineering, Science and Technology. 2010;2:162-183.
[13] Motaghed S, Yazdani A, Nicknam A, Khanzadi M. Sobol sensitivity generalization for engineering and science applications. Journal of Modeling in Engineering. 2018;16:217-226.
[14] Majid Ghoreishi M Z, Vahid Tahmasbi. Sobol Sensitivity Analysis, Modeling and Optimization Effective Parameters of Force in Bone Drilling Processes. Mechanical Engineering Journal of Tabriz University. 2018;48:229-237. (In Persian)
[15] Bathaee S H, Sabzevari M, Moslemi Naeini H. Investigation of hydroforming process loading paths based on experimental and improvement based on Sobol sensitivity analysis. Mechanic of Advanced and Smart Materials. 2022;2:53-72.DOI: 10.52547/masm.2.1.53. (In Persian)
[16] Saltelli A, Sobol I M. About the use of rank transformation in sensitivity analysis of model output. Reliability Engineering & System Safety. 1995;50:225-239.
Mechanic of Advanced and Smart Materials
Volume 2, Issue 2
Summer 2022
Pages 202-219

  • Receive Date 18 July 2022
  • Revise Date 03 August 2022
  • Accept Date 16 August 2022

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