A review of assembly line balancing optimisation with energy consideration using meta-heuristic algorithms

Energy utilisation is one of the global trending issues. Various approaches have been introduced to minimise energy utilisation especially in the manufacturing sector, which is the largest consumer sector. One of the approaches includes the consideration of energy utilisation in the Assembly Line Ba...

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Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture Part B: Journal of Engineering Manufacture, 2022-04, Vol.236 (5), p.475-485
Main Authors: Ramli, Ariff Nijay, Ab Rashid, Mohd Fadzil Faisae
Format: Article
Language:English
Subjects:
Algorithms
Assembly lines
Balancing
Energy
Energy utilization
Heuristic methods
Modelling
Optimization
Social factors
Soft computing
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Summary:Energy utilisation is one of the global trending issues. Various approaches have been introduced to minimise energy utilisation especially in the manufacturing sector, which is the largest consumer sector. One of the approaches includes the consideration of energy utilisation in the Assembly Line Balancing (ALB) optimisation. This paper reviews the ALB with energy consideration from 2012 to 2020. The selected articles were limited to problems solved using meta-heuristic algorithms. The review mainly focusses on the soft computing aspect such as problem variant, optimisation objectives, energy modelling and optimisation algorithm for ALB with energy consideration. Based on the review, the ALB with energy consideration was able to reduce energy utilisation up to 11.9%. It was found that the contribution in future ALB with energy research will be human-oriented, either social factor consideration in optimisation or energy utilisation modelling for workers. In addition, the effort to introduce an algorithm with efficient performance must be pursued because ALB problems have become more complicated. The findings from this review could assist future researchers to align their research direction with the observed trend. This paper also provides the research gap and research opportunities in the future.
ISSN:0954-4054
2041-2975
DOI:10.1177/09544054211040612