Bottleneck easing-based assignment of work and product mixture determination: fuzzy assembly line balancing approach

• Presenting an integrated approach for fuzzy mixed-model ALBP and worker assignment.
• Bottleneck-easing based assignment of works and product-mix.
• Fuzzy RTOC.
• Developing a bi-level fuzzy mathematical model to assign workers and tasks.
• Task times depend on the skill level of workers.

In this study, we propose an integrated heuristic approach for the fuzzy mixed-model assembly line balancing problem. The proposed approach considers bottleneck easing-based assignment of work and product mixture determination by using a fuzzy revised theory of constraints in a capacitated line to maximize the total throughput and minimize the cycle time for the maximum given number of stations. A bi-level fuzzy mathematical model is developed that considers the assignment of workers and tasks, where the task times depend on the skill levels of workers. Furthermore, various probes are used to verify the appropriate selection rules for workers and task assignments using different test problems. The results show that only considering assembly line balancing is not sufficient when capacity constraints are present. Thus, maximization of the available capacity is essential but this should not overload certain stations along the assembly line. The proposed approach is efficient for obtaining good results within a short time.