A simulation-Optimization Based Heuristic to Assign Online Workers Affected by Fatigue in Manufacturing Systems

Journal Article

Ferjani, Aicha . 2017

• المجلة \ الصحيفة: Computers & Industrial Engineering journal

مستخلص المنشور

Manufacturing systems are often characterized by a stochastic and uncertain behavior in which frequent changes and unpredictable events may occur over time. In order to cope with such changes in the manufacturing system state, and to optimize given performance criteria, the assignment of workers to machines can be decided online, in a dynamic manner, whenever workers become available. Several studies, in the ergonomics literature, have outlined that the operators' performances often decline because of their fatigue in work. In manufacturing contexts, fatigue can increase the processing times of jobs. Therefore, we propose to solve the online workers assignment problem through a heuristic, which takes the impact of fatigue into consideration, in order to minimize the mean flowtime of jobs. Thus, the proposed approach suggests computing more realistic task durations, in accordance with the worker's fatigue. Furthermore, this heuristic uses a multi-criteria analysis, in order to find a compromise to favor short process times and to avoid congestions. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used to select the machine where to assign the worker. An adaptation process based on simulation optimization is used to identify weights of the criteria, in TOPSIS, to better fit with the system characteristics. A Job-Shop system is simulated to illustrate the proposed approach. The performance of the suggested heuristic is assessed and compared to two other workers assignment rules widely used in the scientific literature: the SPT and LNQ rules and a sensitivity analysis is performed. Experimental results show the effectiveness of the proposed heuristic