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A Fuzzy Multi-criteria Decision-making Model for Green Electrical Discharge Machining

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Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 335))

Abstract

This paper aims to combine fuzzy and technique for order preference by simulation of ideal solution (TOPSIS) to solve the multi-response parameters optimization problem in green manufacturing. From the viewpoint of health and environment, tap water is used as working fluid, since it does not release the harmful gases. This work considers discharge current, pulse width/pulse interval ratio, gap voltage, and lifting height are the input parameters and output parameters have been identified as material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR). In this paper, initially, an experiment was performed using Taguchi experimental technique. Thereafter, fuzzy-TOPSIS is used to convert multi-response parameters into a single response parameter. Finally, the ranking of the parameter decides the best experimental setup and optimized the input-process parameters. In this work, weighting factors for the output parameters are determined using triangular fuzzy number which influences correlation coefficient values for finding the finest experimental setup. Additionally, an attempt has been made to compare the proposed methodology with the gray relational analysis (GRA). The numerical result shows that the optimum process parameters are A1 (4.5 A), B1 (30:70 μs), C3 (30 V), and D4 (6 mm) and using tap water machining Ti-6Al-4V material can produce high MRR, decrease the machining cost, and have no harmful to the operators and environment.

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Jagadish, Ray, A. (2015). A Fuzzy Multi-criteria Decision-making Model for Green Electrical Discharge Machining. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 335. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2217-0_4

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  • DOI: https://doi.org/10.1007/978-81-322-2217-0_4

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