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Modeling job rotation in manufacturing systems: The study of employee's boredom and skill variations

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  • Azizi, Nader
  • Zolfaghari, Saeed
  • Liang, Ming

Abstract

This paper presents a methodology for job rotation in manufacturing systems that aims to ease employee's boredom and exploit the effect of rotation intervals on worker's skill learning and forgetting. To this end, a series of formulations are proposed to measure employee's boredom and skill variations during a production horizon. Based on the proposed formulations, a mathematical programming model for job rotation is developed, and a numerical example is provided to illustrate its applications. Furthermore, based on a generic framework of the SAMED metaheuristic, a search algorithm, SAMED-JR, is tailored to solve the proposed model for large scale problems.

Suggested Citation

  • Azizi, Nader & Zolfaghari, Saeed & Liang, Ming, 2010. "Modeling job rotation in manufacturing systems: The study of employee's boredom and skill variations," International Journal of Production Economics, Elsevier, vol. 123(1), pages 69-85, January.
    • Handle: RePEc:eee:proeco:v:123:y:2010:i:1:p:69-85
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    References listed on IDEAS

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    Cited by:

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    2. Moreira, Mayron César O. & Costa, Alysson M., 2013. "Hybrid heuristics for planning job rotation schedules in assembly lines with heterogeneous workers," International Journal of Production Economics, Elsevier, vol. 141(2), pages 552-560.
    3. Rubina Zadourian, 2024. "Model-based and empirical analyses of stochastic fluctuations in economy and finance," Papers 2408.16010, arXiv.org.
    4. Jose Antonio Diego-Mas, 2020. "Designing Cyclic Job Rotations to Reduce the Exposure to Ergonomics Risk Factors," IJERPH, MDPI, vol. 17(3), pages 1-17, February.
    5. Marco Trost & Thorsten Claus & Frank Herrmann, 2022. "Social Sustainability in Production Planning: A Systematic Literature Review," Sustainability, MDPI, vol. 14(13), pages 1-31, July.
    6. Corominas, Albert & Olivella, Jordi & Pastor, Rafael, 2010. "A model for the assignment of a set of tasks when work performance depends on experience of all tasks involved," International Journal of Production Economics, Elsevier, vol. 126(2), pages 335-340, August.
    7. Anzanello, Michel J. & Fogliatto, Flavio S. & Santos, Luana, 2014. "Learning dependent job scheduling in mass customized scenarios considering ergonomic factors," International Journal of Production Economics, Elsevier, vol. 154(C), pages 136-145.
    8. Matilda Wollter Bergman & Cecilia Berlin & Maral Babapour Chafi & Ann-Christine Falck & Roland Örtengren, 2021. "Cognitive Ergonomics of Assembly Work from a Job Demands–Resources Perspective: Three Qualitative Case Studies," IJERPH, MDPI, vol. 18(23), pages 1-30, November.
    9. Bel, Roland & Smirnov, Vladimir & Wait, Andrew, 2015. "Team composition, worker effort and welfare," International Journal of Industrial Organization, Elsevier, vol. 41(C), pages 1-8.
    10. Battini, Daria & Berti, Nicola & Finco, Serena & Zennaro, Ilenia & Das, Ajay, 2022. "Towards industry 5.0: A multi-objective job rotation model for an inclusive workforce," International Journal of Production Economics, Elsevier, vol. 250(C).
    11. Heuser, Patricia & Tauer, Björn, 2023. "Single-machine scheduling with product category-based learning and forgetting effects," Omega, Elsevier, vol. 115(C).

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