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CH Smart TV Assembly Line Balance Based On Improved Particle Swarm Optimization

Posted on:2021-03-26Degree:MasterType:Thesis
Country:ChinaCandidate:H L ChenFull Text:PDF
GTID:2428330647963594Subject:Industrial engineering
Abstract/Summary:PDF Full Text Request
After China's accession to the WTO,China's manufacturing industry has developed rapidly,especially electronic and electrical industry,and TVs are one of the most important products of the them.Due to this kind of large-scale production by assembly of parts,the balance rate of the assembly line determines the production efficiency and effectiveness of the entire company.The application of the intelligent optimization algorithm in the assembly line balance has been very mature.This paper uses an improved particle swarm optimization algorithm to optimize the intelligent TV assembly line of CH Company.First of all,this paper analyzes the current situation of assembly line balance,summarizes the development trend of assembly line balance research,and analyzes the current status of CH's smart TV assembly line to summarize the existing problems of the assembly line.Secondly,this paper uses particle swarm optimization as an optimization method to balance the smart TV assembly line of CH Company.Based on the basic particle swarm algorithm,particle swarm algorithm with inertia weight,and particle swarm algorithm with randomly adjusted weights,this paper combines the simulated annealing algorithm to improve the particle swarm algorithm,and obtains a hybrid particle swarm optimization algorithm(SA-PSO)that passed the validity test of four test functions.Finally,this paper set the number of workstations(15,14,13,12,11,and 10)and uses four algorithms to perform 6 calculations,and put forward management suggestions based on the company's current situation and optimization results.The following research results are obtained in the paper.(1)the improved SA-PSO algorithm has faster optimization ability for assembly line balance,can quickly jump out of local solutions,and has better optimization results.(2)Among the calculation results of the six settings and four algorithms,when the number of workstations is 10,the optimization effect of SA-PSO is the best.At this time,the balance rate of the intelligent TV assembly line of CH Company is increased from 37.05% to 91.31%,and workstation load was reduced from 65.84 to 8.64.(3)Three management suggestions were put forward: PDCA cycle management,6S on-site management,and establishment of employee information feedback mechanism.
Keywords/Search Tags:CH smart TV, Assembly line balance, Improved particle swarm optimization, Balance rate, Workstation load
PDF Full Text Request
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