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

58Citations
Citations of this article
53Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

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.

Cite

CITATION STYLE

APA

Majumder, A., Das, P. K., Majumder, A., & Debnath, M. (2014). An approach to optimize the EDM process parameters using desirability-based multi-objective PSO. Production and Manufacturing Research, 2(1), 228–240. https://doi.org/10.1080/21693277.2014.902341

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free