Paper Title:
An Particle Swarm Optimization Approach for Assembly Sequence Planning
  Abstract

Assembly sequence planning (ASP) is the foundation of the assembly planning which plays a key role in the whole product life cycle. Although the ASP problem has been tackled via a variety of optimization techniques, the particle swarm optimization (PSO) algorithm is scarcely used. This paper presents a PSO algorithm to solve ASP problem. Unlike generic versions of particle swarm optimization, the algorithm redefines the particle's position and velocity, and operation of updating particle positions. In order to overcome the problem of premature convergence, a new study mechanism is adopted. The geometrical constraints, assembly stability and the changing times of assembly directions are used as the criteria for the fitness function. To validate the performance of the proposed algorithm, a 29-component product is tested by this algorithm. The experimental results indicate that the algorithm proposed in this paper is effective for the ASP.

  Info
Periodical
Edited by
Kai Cheng, Yongxian Liu, Xipeng Xu and Hualong Xie
Pages
1228-1232
DOI
10.4028/www.scientific.net/AMM.16-19.1228
Citation
H. Yu, J. P. Yu, W. L. Zhang, "An Particle Swarm Optimization Approach for Assembly Sequence Planning", Applied Mechanics and Materials, Vols. 16-19, pp. 1228-1232, 2009
Online since
October 2009
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