Optimization of the Wire Electrical Discharge Machining Process Using Grey Relational Analysis and Taguchi Method

Abstract:

The wire electrical discharge machining is a machining method able to allow detaching parts from plates type workpieces as a consequence of electrical discharges developed between workpiece and wire tool electrode found in a motion along its axis; there is also a work motion along the contour to be obtained. There are many factors able to exert influence on the sizes of parameters of technological interest. On the other hand, there are various methods that can be used in order to establish the optimal combination of the input factors, so that obtaining of machining best results is possible. When there are many process output factors, a problem of multiobjective optimization could be formulated. The Grey relational analysis method and the Taguchi method could be applied in order to optimize the wire electrical discharge machining process, when various criteria having distinct significances are considered. An experimental research was designed and developed in order to optimize the wire electrical discharge cutting of parts made of an alloyed steel, by considering six input factors: test piece thickness, pulse on time, pulse off time, wire axial tensile, current intensity and travelling wire electrode speed. As output parameters, one took into consideration surface roughness, wire tool electrode massic wear, cutting speed along the contour to be obtained. 16 experiments were developed in accordance with the requirements specific to a Taguchi table L16. The results of experiments were processed by means of Grey relational analysis method and Taguchi method.

• Periodical: Key Engineering Materials (Volumes 651-653)
• Pages: 738-743
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.651-653.738
• Online since: July 2015
• Authors: Oana Dodun*, Vasile Merticaru, Laurenţiu Slatineanu, Margareta Coteaţă
• Keywords: Electrical Discharge Machining, Grey Relational Analysis, Input Factors, Process Optimization

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