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A non-zero integer non-linear programming model for maintenance workforce sizing

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  • Ighravwe, D.E.
  • Oke, S.A.

Abstract

This paper formulates a non-linear integer programming model to solve a maintenance workforce sizing problem with a productivity improvement goal. This problem is modelled in a bi-objective framework that minimises the number of maintenance personnel while maximising their productivity levels. Inputs into the optimisation model include monthly and routine maintenance periods, volume of production, contingency maintenance time, use factor and priority factor among others. The model has been validated with real-life detergent factory data, demonstrating its potential usefulness. A principal novelty of the model is the inclusion of use factor, which captures how often maintenance technicians are busy on the job with respect to assigned tasks, including unanticipated high maintenance workload. The model has been solved using a branch and bound algorithm. The impact of workforce structure and workers’ salaries on model’s performance has been studied and sensitivity analysis carried out to investigate the changes to the optimal solution as a result of changes in the input data. The results show a reduction in the number of maintenance workforce personnel in comparing values with and without use factor in the model. The model’s ability to obtain global optimal result depends on the value of the minimum routine maintenance time within each maintenance section. Also, the model is shown to be sensitive to priority factor, which captures the appropriate ratio of full- and part-time workers under the same category. The model provides both an easy-to-use practical tool for maintenance managers and supervisors as well as a scientific tool for determining optimal maintenance workforce size for a manufacturing plant.

Suggested Citation

  • Ighravwe, D.E. & Oke, S.A., 2014. "A non-zero integer non-linear programming model for maintenance workforce sizing," International Journal of Production Economics, Elsevier, vol. 150(C), pages 204-214.
    • Handle: RePEc:eee:proeco:v:150:y:2014:i:c:p:204-214
    DOI: 10.1016/j.ijpe.2014.01.004
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    References listed on IDEAS

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    1. Al-Zubaidi, Hassan & Christer, A. H., 1997. "Maintenance manpower modelling for a hospital building complex," European Journal of Operational Research, Elsevier, vol. 99(3), pages 603-618, June.
    2. Thompson, Gary M. & Goodale, John C., 2006. "Variable employee productivity in workforce scheduling," European Journal of Operational Research, Elsevier, vol. 170(2), pages 376-390, April.
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    Cited by:

    1. He, Xinming & Rizov, Marian & Zhang, Xufei, 2022. "Workforce size adjustment as a strategic response to exchange rate shocks: A strategy-tripod application to Chinese firms," Journal of Business Research, Elsevier, vol. 138(C), pages 203-213.
    2. D. E. Ighravwe & S. A. Oke & K. A. Adebiyi, 2017. "Preventive maintenance task balancing with spare parts optimisation via big-bang big-crunch algorithm," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 811-822, November.
    3. Hesham K. Alfares, 2022. "Plant shutdown maintenance workforce team assignment and job scheduling," Journal of Scheduling, Springer, vol. 25(3), pages 321-338, June.
    4. Desmond Eseoghene Ighravwe & Sunday Ayoola Oke, 2019. "An integrated approach of SWARA and fuzzy COPRAS for maintenance technicians’ selection factors ranking," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(6), pages 1615-1626, December.
    5. D. E. Ighravwe & S. A. Oke, 2017. "A manufacturing system energy-efficient optimisation model for maintenance-production workforce size determination using integrated fuzzy logic and quality function deployment approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(4), pages 683-703, December.
    6. Battaïa, Olga & Delorme, Xavier & Dolgui, Alexandre & Hagemann, Johannes & Horlemann, Anika & Kovalev, Sergey & Malyutin, Sergey, 2015. "Workforce minimization for a mixed-model assembly line in the automotive industry," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 489-500.

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