Parameters Optimization of Electrical Discharge Machining Process Using Swarm Intelligence: A Review

Author:

Chen Yanyan1,Hu Shunchang23,Li Ansheng23,Cao Yang3,Zhao Yangjing3,Ming Wuyi34

Affiliation:

1. College of Mechanical Engineering, Yellow River Conservancy Technical Institute, Kaifeng 475000, China

2. Hydropower Equipment and Intelligent System Engineering Technology Research Centre of Henan Province, Department of Mechanical and Electronic Engineering, Henan Vocational College of Water Conservancy and Environment, Zhengzhou 450002, China

3. Mechanical and Electrical Engineering Institute, Zhengzhou University of Light Industry, Zhengzhou 450002, China

4. Guangdong Provincial Key Laboratory of Digital Manufacturing Equipment, Guangdong HUST Industrial Technology Research Institute, Dongguan 523808, China

Abstract

Electrical discharge machining (EDM) can use soft tool electrodes to process hard workpieces to achieve “soft against hard”, because it directly uses electrical energy and thermal energy to remove metal materials. Then, it can generate complex features on harder materials and meet the requirements of excellent surface quality. Since EDM involves many process parameters, including electrical parameters, non-electrical parameters, and materials properties, it is essential to optimize its process parameters to obtain good performance. In this direction, the application of the swarm intelligence (SI) technique has become popular. In this paper, the existing literature is comprehensively reviewed, and the application of the SI technique in the optimization of EDM process parameters is summarized. Sinker-EDM (SEDM), wire-EDM (WEDM), and micro-EDM (MEDM) with various hybrid techniques are among the EDM methods considered in this study because of their broad adoption in industrial sections. The fundamental nature of all review articles will assist engineers/workers in determining the process parameters and processing performance, the SI algorithm, and the optimal technique by which to obtain the desired process parameters. In addition, discussions from the perspectives of the similarity, individuality, and complementarity of various SI algorithms are proposed, and necessary outlooks are predicted, which provides references for the high performance of the EDM processes in the future.

Funder

Local Innovative and Research Teams Project of Guangdong Pearl River Talents Program

Guangdong Basic and Applied Basic Research Foundation

Science and Technology Project of Henan Province

Publisher

MDPI AG

Subject

General Materials Science,Metals and Alloys

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