Experimental modelling and multi-objective optimisation of electrochemical discharge peripheral surface grinding process during machining of alumina epoxy nanocomposites

被引：0
作者：
Singh N. [1 ,2 ]
Yadava V. [1 ,2 ]
Shandilya P. [1 ,2 ]
机构：
[1] Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Prayagraj, Allahabad
[2] Department of Mechanical Engineering, Motilal Nehru National Institute of Technology, Prayagraj, Allahabad
来源：
International Journal of Industrial and Systems Engineering | 2024年 / 47卷 / 03期
关键词：
desirability function analysis; DFA; ECDM; ECDPSG; GRA; Grey relational analysis; grinding; multi-objective optimisation; polymer nanocomposite; PSN; response surface methodology; RSM;
D O I：
10.1504/IJISE.2024.139562
中图分类号：
学科分类号：
摘要：
Machining electrically non-conductive materials is still a very challenging task. So far, electrochemical discharge machining (ECDM) and its configurations, such as drilling-ECDM, TW-ECDM, and milling-ECDM, have been developed for machining such materials. Hence, an in-depth experimental analysis of grinding-ECDM is also required. In the present work, the mathematical models have been formulated using response surface methodology based on Box-Behnken design on the peripheral surface configuration of grinding-ECDM (electrochemical discharge peripheral surface grinding process). Experiments were carried out on alumina-reinforcement epoxy nanocomposites considering supply voltage, pulse on-time, electrolyte concentration, and wheel rotation as input process parameters and MRR and Ra as output performance parameters. The multi-objective optimisation has been done using desirability function analysis (DFA) and grey relational analysis (GRA). The input process parametric conditions obtained from both optimisation methods are different. It has been found that DFA shows slightly better results than GRA for both MRR and Ra. Copyright © 2024 Inderscience Enterprises Ltd.
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页码：404 / 420
页数：16
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