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Multi-objective parametric optimization on machining with wire electric discharge machining

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Abstract

The selection of optimum machining conditions, during wire electric discharge machining process, is of great concern in manufacturing industries these days. The increasing quality demands, at higher productivity levels, require the wire electric discharge machining process to be executed more efficiently. Specifically, the material removal rate needs to be maximized while controlling the surface quality. Despite extensive research on wire electric discharge machining process, determining the desirable operating conditions in industrial setting still relies on the skill of the operators and trial-and-error methods. In the present work, an attempt has been made to optimize the machining conditions for maximum material removal rate and maximum surface finish based on multi-objective genetic algorithm. Experiments, based on Taguchi’s parameter design, were carried out to study the effect of various parameters, viz. pulse peak current, pulse-on time, pulse-off time, wire feed, wire tension and flushing pressure, on the material removal rate and surface finish. It has been observed that a combination of factors for optimization of each performance measure is different. So, mathematical models were developed between machining parameters and responses like metal removal rate and surface finish by using nonlinear regression analysis. These mathematical models were then optimized by using multi-objective optimisation technique based on Non-dominated Sorting Genetic Algorithm-II to obtain a Pareto-optimal solution set.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Bundelkhand Institute of Engineering and Technology, Jhansi, 284 128, India

    Kapil Kumar & Sanjay Agarwal

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  1. Kapil Kumar
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  2. Sanjay Agarwal
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Correspondence to Sanjay Agarwal.

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Kumar, K., Agarwal, S. Multi-objective parametric optimization on machining with wire electric discharge machining. Int J Adv Manuf Technol 62, 617–633 (2012). https://doi.org/10.1007/s00170-011-3833-1

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  • DOI: https://doi.org/10.1007/s00170-011-3833-1

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