Title: Wolf pack algorithm for optimisation of cutting parameters in WEDM using Taguchi method

Authors: Yanqiu Xiao; Wuyi Ming; Dili Shen; Wenbin He; Jun Ma; Jianqiang Jiao

Addresses: Department of Electromechanical Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China ' Guangdong HUST Industrial Technology Research Institute, Guangdong Provincial Key Laboratory of Digital Manufacturing Equipment, Dongguan, 523808, China ' School of Mechanical-electronic and Automobile Engineering, Zhengzhou Institute of Technology, Zhengzhou, 450015, China ' Department of Electromechanical Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China ' Department of Electromechanical Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China ' Department of Electromechanical Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, China

Abstract: The optimisation of cutting parameters for wire electrical discharge machining (WEDM) is one the most difficult combinatorial optimisation problems, due to their complicated, coupled and nonlinear nature of the input-output variables of them. An exact solution for a WEDM optimisation problem cannot be easily obtained within a reasonable amount of time. Therefore, a meta heuristic algorithm is required [e.g., genetic algorithm (GA), particle swarm optimisation (PSO), wolf pack algorithm (WPA), etc.)]. The objective of this paper is to develop a robust approach using WPA to obtain the optimised combination of cutting parameters for the process of WEDM. Hence, a Taguchi orthogonal array is proposed instead of a full factorial experimental design for determining the parameters of the WPA. The effects of the WPA parameters on optimising the cutting parameters are disclosed and an analysis of variance is performed to investigate significance factors on the results. By experiments of WEDM, an application was presented to illustrate the effectiveness of the proposed approach. Compared with the S/N ratio statistical method of reported previously, the performance of Ra and material removal rate (MRR) were improved by 12% and 3.99%, respectively.

Keywords: combinatorial optimisation; wolf pack algorithm; WPA; Taguchi orthogonal method; wire electrical discharge machining; WEDM.

DOI: 10.1504/IJIMS.2019.098226

International Journal of Internet Manufacturing and Services, 2019 Vol.6 No.2, pp.139 - 154

Received: 13 Apr 2017
Accepted: 03 Mar 2018

Published online: 07 Jan 2019 *

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