Assembly sequence planning method based on particle swarm algorithm

2017 ◽  
Vol 22 (S1) ◽  
pp. 835-846 ◽  
Author(s):  
Yu-jia Wu ◽  
Yan Cao ◽  
Qiang-feng Wang
Keyword(s):  
Particle Swarm ◽  
Assembly Sequence Planning ◽  
Planning Method ◽  
Particle Swarm Algorithm ◽  
Assembly Sequence ◽  
Sequence Planning ◽  
Swarm Algorithm

A Particle Swarm Algorithm for Assembly Sequence Planning

2010 ◽  
Vol 97-101 ◽  
pp. 3243-3246
Author(s):  
Yan Feng Xing ◽  
Yan Song Wang ◽  
Xiao Yu Zhao
Keyword(s):  
Particle Swarm ◽  
Tolerance Analysis ◽  
Assembly Sequence Planning ◽  
Particle Swarm Algorithm ◽  
Assembly Sequence ◽  
Sequence Generation ◽  
Assembly Sequences ◽  
Swarm Algorithm ◽  
Assembly Sequence Generation ◽  
Optimal Assembly

A particle swarm algorithm is proposed to generate optimal assembly sequences for compliant assemblies. Firstly, the liaison graph and the adjacency matrix describe the geometry of the compliant assemblies. An assembly sequence is represented by a character string, whose length is the number of all parts. The conceptual tolerance analysis is used to evaluate feasible sequences. Thereafter, the particle swarm algorithm is presented to generate assembly sequences, in which the elite ratio is applied to improve optimization results. Finally a fender assembly is used to illustrate the algorithm of assembly sequence generation and optimization.

scholarly journals Multi-objective discrete particle swarm optimisation algorithm for integrated assembly sequence planning and assembly line balancing

2016 ◽  
Vol 232 (8) ◽  
pp. 1444-1459 ◽  
Author(s):  
Mohd Fadzil Faisae Ab Rashid ◽  
Windo Hutabarat ◽  
Ashutosh Tiwari
Keyword(s):  
Assembly Line ◽  
Particle Swarm ◽  
Assembly Line Balancing ◽  
Particle Swarm Optimisation ◽  
Assembly Sequence Planning ◽  
Line Balancing ◽  
Assembly Sequence ◽  
Discrete Particle ◽  
Sequence Planning ◽  
Multi Objective

In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs. Both activities are categorised as NP-hard and usually performed separately. Assembly sequence planning and assembly line balancing optimisation presents a good opportunity to be integrated, considering the benefits such as larger search space that leads to better solution quality, reduces error rate in planning and speeds up time-to-market for a product. In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set.

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