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Developing a multi-objective genetic optimisation approach for an operational design of a manual mixed-model assembly line with walking workers

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Abstract

A walking worker assembly line (WWAL), in which each cross-trained worker travels along the line to carry out all required tasks, is an example of lean system, specifically designed to respond quickly and economically to the fluctuating nature of market demands. Because of the complexity of WWAL design problems, classical heuristic approaches are not capable of solving problematic design characteristic of WWAL of very large design space. This paper presents a new genetic approach to address the mixed model walking worker manual assembly line optimisation design problem with multiple objectives. The aim is to select a set of operational variables to perform to the required demand for two product models. The goal is to produce the required models at the lowest cost possible, whilst keeping within an ergonomically balanced operation. Genetic algorithms are developed to tackle this problem. This paper describes the fundamental structure of this approach, as well as the influence of the crossover probability, the mutation probability and the size of the population on the performance of the genetic algorithm. The paper also presents an application of a developed algorithm to the operational design problem of plastic electrical box assembly line.

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Acknowledgments

The authors would like to express their appreciation to anonymous referees for their helpful comments.

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Authors and Affiliations

  1. School of Engineering, University of South Australia, Mawson Lakes, SA, 5095, Australia

    Atiya Al-Zuheri, Lee Luong & Ke Xing

  2. Ministry of Science and Technology, Al-Jadriya, 10070 , Baghdad, Iraq

    Atiya Al-Zuheri

Authors
  1. Atiya Al-Zuheri
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  2. Lee Luong
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  3. Ke Xing
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Correspondence to Atiya Al-Zuheri.

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Al-Zuheri, A., Luong, L. & Xing, K. Developing a multi-objective genetic optimisation approach for an operational design of a manual mixed-model assembly line with walking workers. J Intell Manuf 27, 1049–1065 (2016). https://doi.org/10.1007/s10845-014-0934-3

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  • DOI: https://doi.org/10.1007/s10845-014-0934-3

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