Open AccessAn Assembly Line Multi-Station Assembly Sequence Planning Method Based on Particle Swarm Optimization Algorithm
Author(s) -
Shuan-Jun Song Shuan-Jun Song,
Cheng-Hong Qiu Shuan-Jun Song,
Long-Guang Peng Cheng-Hong Qiu,
Sheng Peng
Publication year - 2022
Publication title -
diànnǎo xuékān/diannao xuekan
Language(s) - English
Resource type - Journals
eISSN - 2312-993X
pISSN - 1991-1599
DOI - 10.53106/199115992022023301011
Subject(s) - assembly line , particle swarm optimization , sequence (biology) , algorithm , swarm behaviour , line (geometry) , scheme (mathematics) , engineering , function (biology) , fitness function , sequence assembly , mathematical optimization , computer science , genetic algorithm , mathematics , mechanical engineering , biology , mathematical analysis , geometry , evolutionary biology , genetics , biochemistry , gene expression , transcriptome , gene
Aiming at the problem that the existing assembly sequence planning methods are difficult to meet the multi-station assembly requirements of assembly line, an assembly sequence planning method of assembly line considering the constraints of station sequence and station capability is proposed. The multi-station assembly sequence model is established to describe the allocation scheme and assembly sequence of parts. The conditions and generating rules of feasible assembly sequence are given. The assembly time variance of each station is used as the fitness function, and the particle swarm optimization (PSO) algorithm is designed. Taking an engineering vehicle assembly as an example, the optimal integration solution of multi-station assembly sequence and job assignment is obtained by using this algorithm, and the validity of the model is verified.