Optimal parameter prediction of oxygen-mist near-dry wire-cut EDM

S. Boopathi and K. Sivakumar

International Journal of Manufacturing Technology and Management, 2016, vol. 30, issue 3/4, 164-178

Abstract: Wire-cut electrical discharge machining (WEDM) is one of the important non-traditional machining processes to cut hard and high strength materials. It was observed from the literature that some environmental pollutants had been emitted owing to thermal decomposition of the liquid dielectric mediums used in WEDM. In this near-dry WEDM process, oxygen-mist is used as a dielectric medium which encourages the eco-friendly cutting process owing to minimal usage of liquid-based dielectric medium. In this paper, the experiments have been performed using the compressed oxygen gas mixed with minimum quantity of demineralised water as a dielectric medium. The design of experiments has been performed using Taguchi's L27 orthogonal array. The spark-current, pulse-on-time, oxygen-mist inlet pressure and mixing flow rate are selected as input parameters, and material removal rate and surface roughness are considered as response characteristics. After the experimentation, the regression analysis has been employed to develop the best mathematical models for the multi-objective optimisation purpose. Multi-objective artificial bee colony (MOABC) algorithm is introduced to predict the optimal set of input and output parameters using non-dominated Pareto-optimal-front solutions.

Keywords: near-dry WEDM; oxygen mist; Taguchi methods; multi-objective ABC; MOABC; artificial bee colony; Pareto optimal front; optimal parameters; parameter prediction; wire EDM; electrical discharge machining; electro-discharge machining; eco-friendly cutting; compressed oxygen gas; demineralised water; dielectric medium; design of experiments; DOE; orthogonal arrays; spark current; pulse-on-time; inlet pressure; mixing flow rate; material removal rate; MRR; surface roughness; surface quality; mathematical modelling. (search for similar items in EconPapers)
Date: 2016
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