Optimization of ECM Process Parameters Using NSGA-II

Abstract

Electrochemical machining (ECM) could be used as one of the best non-traditional machining technique for machining electrically conducting, tough and difficult to machine material with appropriate machining parameters combination. This paper attempts to establish a comprehensive mathematical model for correlating the interactive and higher-order influences of various machining parameters on the predominant machining criteria, i.e. metal removal rate and surface roughness through response surface methodology (RSM). The adequacy of the developed mathematical models has also been tested by the analysis of variance (ANOVA) test. The process parameters are optimized through Nondominated Sorting Genetic Algorithm-II (NSGA-II) approach to maximize metal removal rate and minimize surface roughness. A non-dominated solution set has been obtained and reported.

Multiobjective Optimization of Heat-Treated Copper Tool Electrode on EMM Process Using Artificial Bee Colony (ABC) Algorithm

“…Analysis of variance is a statistically based decision-making tool used to detect any deviations in the mean performance of a group of items that have been tested. ANOVA compares the mean square against the estimate of the experimental errors at set confidence levels, thus aiding in the identification of significance of the main factors and their interactions in a study [ 47 , 48 ]. where n is the no.…”

Optimasi Kekasaran Permukaan Baja AISI H13 pada Proses Permesinan Elektro Kimia Skala Laboratorium dengan Metode Taguchi

“…Optimasi parameter dilakukan dengan pendekatan NGSA-II. Hasilnya menunjukkan optimalisasi MRR dan kekasaran permukaan (Ra) meningkatkan tingkat produksi dengan waktu permesinan dapat dikurangi [4].…”

Application of MCDM-Based TOPSIS Method for the Optimization of Multi Quality Characteristics of Modern Manufacturing Processes

“…Most of the NTM processes (also called modern manufacturing processes) comprise of multiple input and output characteristics. The input characteristics play an important role in obtaining the good quality and productivity (Senthilkumar et al, 2013;Chandra et al, 2011;Bhosale et al, 2014). Therefore, selecting an appropriate combination of process variables becomes first priority in production sectors.…”

“…AJM, AWJM, ECM, ECMM, LBM, EDM, WEDM, USM, etc. (Zain et al, 2011;Joshi et al, 2011;Rao et al, 2009;Kuriakose and Shunmugan, 2005;Aich et al, 2014;Senthilkumar et al, 2011), but none of them have used TOPSIS approach for the optimization of NTM processes, so far. Therefore, an attempt has been made in the present study to explore the applicability, durability and flexibility of TOPSIS method in optimization of some modern machining processes.…”