An Extensive Review of Various Optimization Techniques for Electric Discharge Machining

Author:

Singh Abhishek1,Garg Rajiv Kumar1,Sachdeva Anish1

Affiliation:

1. Department of Industrial and Production Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India.

Abstract

In this paper, an investigation of wire and electric discharge machining has been provided. Wider possibilities for the creation of composites and sophisticated materials were made possible by advances in machining science. As research in this area continues, more materials with complicated meteorological structures and strong mechanical resistance capabilities are emerging. Because of the exceptional strength, toughness, and hardness of these materials, advanced machining techniques are replacing traditional machining techniques in this industry. One unique type of advanced machining technique used in this research is electrical discharge machining. It has also been discussed how these machining methods might develop in the future. This paper serves as both a research tool and a step in that direction. The best settings for the processes outlined above will aid in boosting diverse sectors' output. The research on non-conventional machining processes with diverse optimisation strategies is presented in this review. The optimisation techniques taken into account for the current work were Taguchi's, artificial neural networks, particle swarm optimisation, response surface approach, grey connection analysis, and genetic algorithm.

Publisher

Ram Arti Publishers

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3