Model and heuristics for the multi-manned assembly line worker integration and balancing problem.
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| Title: | Model and heuristics for the multi-manned assembly line worker integration and balancing problem. |
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| Authors: | Michels, Adalberto Sato1,2 (AUTHOR) a.satomichels@unimelb.edu.au, Costa, Alysson M.1,2 (AUTHOR) |
| Source: | International Journal of Production Research. Dec2024, Vol. 62 Issue 24, p8719-8744. 26p. |
| Subjects: | Assembly line balancing, Assembly line methods, Linear programming, Manufacturing industries, Labor supply |
| Abstract: | This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce. Both topics received considerable attention in the literature, but not in an integrated fashion. Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem. When considering multi-manned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments. We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach. Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times. We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences. From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | This paper examines the balancing of assembly lines with multi-manned stations and a heterogeneous workforce. Both topics received considerable attention in the literature, but not in an integrated fashion. Combining these two characteristics gives rise to a highly combinatorial Multi-manned Assembly Line Worker Integration and Balancing Problem. When considering multi-manned stations, the already coupled decisions on assigning tasks to heterogeneous workers and workers to stations must be further linked with task scheduling assessments. We propose a Mixed-Integer Linear Programming model and develop two heuristic solution procedures, which tackle the problem with a hierarchical decomposition approach. Computational tests on a large dataset indicate that the proposed method can obtain good primal bounds in short computational times. We demonstrate that these results can be applied to the monolithic model either as a warm start or in a proximity search procedure to obtain synergistic gains with statistically significant differences. From a managerial perspective, we show that multi-manned stations can reduce the assembly line's length even in the presence of a heterogeneous workforce, which is crucial for many industries manufacturing large-size products. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00207543 |
| DOI: | 10.1080/00207543.2024.2347572 |
