Workforce scheduling incorporating worker skills and ergonomic constraints. (June 2022)

• Record Type: Journal Article
• Authors: Rinaldi, Marta; Fera, Marcello; Bottani, Eleonora; Grosse, Eric H.
• Is Part Of: Computers & industrial engineering. Volume 168(2022)
• Publication Date: 2022-06
• Subjects: Ergonomics -- Human skill -- Human performance -- Workforce assignment -- Empirical study; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108107
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A novel approach is proposed to model human performance. A constructive heuristic procedure has been developed to solve a real-life problem. The performance of the system improves when integrating ergonomics and human skills. A limited decrease in the makespan allows balancing the workload among workers. Abstract: In the last few decades, studies have demonstrated the correlation between worker well-being and the performance of production systems. This paper addresses the problem of assigning workers to tasks in a workshop system. In this context, recent researches have focused on the ergonomics assessment, often neglecting the evaluation of the workers' performance. This study aims to formulate a mixed integer linear programming model to solve the workforce scheduling problem and improve the performance of the system integrating ergonomics and human skills. To overcome the complexity of the combinatorial problem, a constructive heuristic procedure is developed. Moreover, a novel approach is proposed to determine the workers' skills. Human performance is modelled in terms of the time required to perform consecutive tasks, considering different sequences of tasks. In addition, the model was applied to a real case study to verify its feasibility. Different scenarios are tested, considering different levels of exposure to different risk factors. The results indicate that a limited increase in the makespan enables decreasing the risk level and the achievement of an excellent workload balance among workers in terms of time spent in performing tasks. Moreover, the heuristic procedure has demonstrated to perform well on instances of realistic size, and it could be adapted to many manufacturing systems to solve the problem in real industrial contexts.