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Journal of Intelligent Manufacturing

, Volume 30, Issue 1, pp 291–302 | Cite as

ErgoALWABP: a multiple-rule based constructive randomized search algorithm for solving assembly line worker assignment and balancing problem under ergonomic risk factors

  • Sebnem Demirkol Akyol
  • Adil BaykasoğluEmail author
Article

Abstract

This paper proposes a new type of assembly line worker assignment and balancing problem (ALWABP) which considers ergonomic risks. ALWABP occurs when task times vary according to the assigned worker. Although the operation time of a task is assumed to be fixed in classical assembly lines, it depends on the operator who executes the task in ALWABP. In ALWABP literature, the primary and secondary objectives are minimizing cycle time and balancing workload among workstations smoothly, respectively. When smoothing workload, only task times are taken into consideration in the relevant literature. However, degree of difficulty of tasks is also very important. Two workers executing two different stations with the same station time are assumed to be equally loaded according to the traditional perception. In fact, even they have the same station time; their workloads are different because of the different tasks they execute, in real life assembly line configurations. In order to close this gap between the real life and the literature, this study introduces an ALWABP problem with considering ergonomic risk factors (ErgoALWABP). Due to the complex nature of the problem, optimum seeking methods are not capable of solving it. So, the proposed problem is tackled with the multiple-rule based constructive randomized search approach. Also, OCcupational Repetitive Action method is used for making ergonomic risk assessment. Performance of the proposed solution procedure is compared with the relevant literature on benchmark data. Experimental results show that ergonomic environment could be improved when ergonomic risk factors are taken into account.

Keywords

Assembly line balancing Worker assignment Ergonomic risk assessment Multi-objective optimization Heuristic approaches Combinatorial optimization 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of Industrial EngineeringDokuz Eylül UniversityIzmirTurkey

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