Incorporating uncertain human behavior in production scheduling for enhanced productivity in Industry 5.0 context

Abstract

Human-centered production systems are of increasing interest to researchers, especially with the advent of the Industry 5.0 paradigm. Most research into production scheduling has long neglected human workers’ specific roles and unpredictable behavior in a production system, treating them as machines with deterministic behavior. This work studies the impact of human operational behavior on the performance of a production system and proposes an optimization model to allocate workers’ profiles to workstations. We modeled the punctuality profile as a Markov chain representing a worker’s productive and non-productive states. We developed a simulation process based on the multi-agent system (MAS) paradigm to test the effectiveness of the proposed model and to measure the impact of workers’ behaviors and their assignments to different workstations on the productivity of the workshop. A non-linear programming model is also proposed to provide the optimal assignment of workers to workstations while maximizing the throughput of a dual-resource-constrained flow-shop production system for a given mix of production. The results obtained highlight the significant impact of human operator behavior on the performance of a production system. The findings demonstrate the importance of incorporating human behavior models into the decision-making process for assigning workers to workstations based on their operational profiles.