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Optimization of Process Parameters Using Hybrid Taguchi and VIKOR Method in Electrical Discharge Machining Process

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Advanced Engineering Optimization Through Intelligent Techniques

Abstract

Electrical discharge machining (EDM), based on thermal erosion principle, is used to machine materials in the area of aerospace, surface texturing, die, and mold manufacturing. In this work, an attempt is made to use oil extracted from vegetable as dielectric fluid and to carry out optimization study of EDM using Taguchi-based hybrid optimization technique. Taguchi optimization method is a statistical approach to determine optimum process parameters, but it is appropriate for solving single-objective problem. Most of the manufacturing industries problems are involved with multiple objectives. Hence, Taguchi method must unite with some other techniques such as gray relational approach, desirability function, and utility concept to multiple objectives. Taguchi method is combined with VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian (VIKOR) for solving multiple objectives simultaneously. The performance of commercial dielectric fluid (kerosene) is compared with two different types of vegetable oils such as Jatropha oil and cottonseed oil. Copper is selected as electrode material which is cryogenically treated and tempered. The result showed that the proposed approach has easy computational steps for solving multiple objectives simultaneously and the same can be applicable to other machining process parameter optimizations.

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Acknowledgements

The authors would like to thank IEI R&D cell for supporting and funding this research work. Ref.: RDPG2017006.

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Correspondence to B. Singaravel .

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Singaravel, B., Deva Prasad, S., Chandra Shekar, K., Mangapathi Rao, K., Gowtham Reddy, G. (2020). Optimization of Process Parameters Using Hybrid Taguchi and VIKOR Method in Electrical Discharge Machining Process. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_46

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