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An improved discrete particle swarm optimization algorithm for high-speed trains assembly sequence planning

Mingyu Li (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan, China)
Bo Wu (The State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China)
Pengxing Yi (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan, China)
Chao Jin (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan, China)
Youmin Hu (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan, China)
Tielin Shi (School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan, China)

Assembly Automation

ISSN: 0144-5154

Article publication date: 23 September 2013

471

Abstract

Purpose

In the high-speed trains (HSTs) production process, assembly sequence planning (ASP) problems is an extremely core issue. ASP problems influence the economic cost, amount of workers and the working time in the assembly process, seriously. In the design process of HSTs, the assembly sequence is usually given by experience, and the correctness of the assembly sequence is difficult to guarantee by experience and low effectiveness. The ASP based on improved discrete particle swarm optimization (IDPSO) algorithm was proposed to address these issues.

Design/methodology/approach

In view of the local convergence problem with basic DPSO in ASP, this paper presents an IDPSO, in which a chosen strategy of global optimal particle is introduced in, to solve the ASP problems in the assembly process of HSTs operation panel. The geometric feasibility, the assembly stability, and the number of assembly orientation changes of the assembly are chosen to be the optimization objective. Furthermore, the influences of the population size, the weight coefficient, and the learning factors to the stability and efficiency of IDPSO algorithm were discussed.

Findings

The results show that the IDPSO algorithm can obtain the global optimum efficiently, which is proved to be a more useful method for solving ASP problems than basic DPSO. The IDPSO approach could reduce the working time and economic cost of ASP problems in HSTs significantly.

Practical implications

The method may save the economic cost, reduce the amount of workers and save the time in the assembly process of HSTs. And also may change the method of ASP in design and manufacturing process, and make the production process in HSTs more efficiently.

Originality/value

A chosen strategy of global optimal particle is presented, which can overcome the local convergence problem with basic DPSO for solving ASP problems.

Keywords

Acknowledgements

This work is sponsored by the National Key Technology R&D Program of China, Grant No. 2009BAG12A01-G01-3. And very grateful acknowledge the Tangshan Railway Vehicle Co., Ltd and CSR Sifang Locomotive & Rolling Stock Co., Ltd

Citation

Li, M., Wu, B., Yi, P., Jin, C., Hu, Y. and Shi, T. (2013), "An improved discrete particle swarm optimization algorithm for high-speed trains assembly sequence planning", Assembly Automation, Vol. 33 No. 4, pp. 360-373. https://doi.org/10.1108/AA-07-2012-062

Publisher

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Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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