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Integrated optimization of mixed-model assembly sequence planning and line balancing using Multi-objective Discrete Particle Swarm Optimization

Published online by Cambridge University Press:  06 May 2019

Mohd Fadzil Faisae Ab Rashid ,
Ashutosh Tiwari  and
Windo Hutabarat
Mohd Fadzil Faisae Ab Rashid*
Affiliation:
Faculty of Mechanical Engineering, Universiti Malaysia Pahang, 26600 Pekan, Malaysia
Ashutosh Tiwari
Affiliation:
Manufacturing and Materials Department, Cranfield University, Bedford MK43 0AL, UK
Windo Hutabarat
Affiliation:
Manufacturing and Materials Department, Cranfield University, Bedford MK43 0AL, UK
*
Author for correspondence: Mohd Fadzil Faisae Ab Rashid, E-mail: ffaisae@ump.edu.my
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Abstract

Recently, interest in integrated assembly sequence planning (ASP) and assembly line balancing (ALB) began to pick up because of its numerous benefits, such as the larger search space that leads to better solution quality, reduced error rate in planning, and expedited product time-to-market. However, existing research is limited to the simple assembly problem that only runs one homogenous product. This paper therefore models and optimizes the integrated mixed-model ASP and ALB using Multi-objective Discrete Particle Swarm Optimization (MODPSO) concurrently. This is a new variant of the integrated assembly problem. The integrated mixed-model ASP and ALB is modeled using task-based joint precedence graph. In order to test the performance of MODPSO to optimize the integrated mixed-model ASP and ALB, an experiment using a set of 51 test problems with different difficulty levels was conducted. Besides that, MODPSO coefficient tuning was also conducted to identify the best setting so as to optimize the problem. The results from this experiment indicated that the MODPSO algorithm presents a significant improvement in term of solution quality toward Pareto optimal and demonstrates the ability to explore the extreme solutions in the mixed-model assembly optimization search space. The originality of this research is on the new variant of integrated ASP and ALB problem. This paper is the first published research to model and optimize the integrated ASP and ALB research for mixed-model assembly problem.

Keywords

Assembly sequence planningconcurrent optimizationline balancingmanufacturing systemsParticle Swarm Optimization
Type
Research Article
Information
AI EDAM , Volume 33 , Issue 3 , August 2019 , pp. 332 - 345
Copyright
Copyright © Cambridge University Press 2019 

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