Integrating workers' differences into workforce planning

In today's competitive market, manufacturers need to work hard towards improving their production system performance in order to satisfy customer demands. In such a situation, most companies develop production systems that can help in quality improvement, cost reduction and throughput time reduction. In this research, we consider a workforce planning (WP) model including some human aspects such as skills, training, and workers' personalities and motivation. A multi-objective non-linear programming model is developed in order to minimize the hiring, firing, training and overtime costs and minimize the number of fired most productive workers. The purpose is to determine the number of workers for each worker type, the number of workers trained, and the number of overtime hours. Moreover, a decision support system (DSS) based on the proposed model is introduced using the Excel-LINGO software interfacing feature. The results indicate that the proposed model can provide a promising workforce planning approach to easily apply it in practice.

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