An approach to optimize the EDM process parameters using desirability-based multi-objective PSO

被引：43

作者：

Majumder, Arindam ^{[1
]}

Das, Pankaj Kumar ^{[1
]}

Majumder, Abhishek ^{[2
]}

Debnath, Moutushee ^{[1
]}

机构：

[1] Natl Inst Technol Agartala, Mech Engn Dept, Agartala 799055, India

[2] Tripura Univ, Dept Comp Sci & Engn, Agartala, India

来源：

PRODUCTION AND MANUFACTURING RESEARCH-AN OPEN ACCESS JOURNAL | 2014年 / 2卷 / 01期

关键词：

EDM; MRR; EWR; optimization; desirability-based multi-objective particle swarm optimization-original; desirability-based multi-objective particle swarm optimization-inertia weight; desirability-based multi-objective particle swarm optimization-constriction factor;

D O I：

10.1080/21693277.2014.902341

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The present work deals with the prediction of optimal parametric data-set with maximum material removal rate (MRR) and a minimum electrode wear ratio (EWR) during Electrical discharge machining (EDM) of AISI 316LN Stainless Steel. For this purpose, empirical models showing relation between inputs and outputs were developed using response surface methodology. Desirability-based multi-objective particle swarm optimization-original, desirability-based multi-objective particle swarm optimization-inertia weight, and desirability-based multi-objective particle swarm optimization-constriction factor are then used to estimate the optimal process parameters for maximum MRR and minimum EWR. The results obtained by applying these three desirability-based multi-objective particle swarm optimization (DMPSO) algorithms are compared. From the comparison and confirmatory experiment, it can be observed that DMPSO-CF is the most efficient algorithm for the optimization of EDM parameters.

引用

页码：228 / 240

页数：13

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