Simulation-based optimization of workforce configuration for multi-division maintenance departments

2024-02-01
Gölbaşı, Onur
Sahiner, Sahin Furkan
The configuration of human resources in a production company that determines the number of employees at different technical or nontechnical competencies engaged in various operational tasks should be constructed to meet the task requirements above pre-specified expectation levels. Human resource requirements show variation depending on the divisional structures within an organization and their operational dependencies and priorities. A maintenance facility is generally recognized as one of the most labor-intensive divisions in any production company. It employs several workers with diverse technical skills to ensure machinery reliability and availability targets in line with the production plans. The current research study aims to develop a continuous-eventsimulation algorithmto optimize the maintenance crew configuration and allocation decisions for production companies where different clusters of failure modes are available for multi-equipment operations. This algorithm also simultaneously evaluates the reallocation of the occupied crew for other overlapping maintenance tasks that require similar technical competency. Accordingly, each maintenance division with varying personnel numbers is authorized to maintain particular failure modes. The developed model was implemented for the maintenance department of a surface coal mine where fiveexcavatorsexposed to diversified random failures are employed. The model input dataset covers three years of maintenance records classified into mechanical and electrical failure modes. The simulation outcomes reveal that the cumulative indirect and direct costs can be minimized for a crew configuration including six electricians and four mechanics.
COMPUTERS & INDUSTRIAL ENGINEERING
Citation Formats
O. Gölbaşı and S. F. Sahiner, “Simulation-based optimization of workforce configuration for multi-division maintenance departments,” COMPUTERS & INDUSTRIAL ENGINEERING, vol. 188, no. 1, pp. 109880–109880, 2024, Accessed: 00, 2024. [Online]. Available: https://doi.org/10.1016/j.cie.2024.109880.