Decision making in operator-machine assignment problems: an optimization approach in U-shaped production lines

Abstract

Decision-making is a complex problem in all fields of production, because decision makers have to find the most suitable solution alternative among the numerous, while the solution of the problem is limited by multiple, usually conflicting constraints. In the Industry 4.0 era, one of the most widely used production lines are the U-shaped production lines, which focus on the elimination of waste through a high utilization of workers. It means, that worker-machine assignment plays a significant role in the optimization of production processes in a U-shaped production line. The current investigation proposes a novel absorbing Markov chain (AMC) optimization approach to support the decision making regarding worker selection and assignment. The proposed approach integrates the AMC and the performance analysis of the production process. The numerical results validated the decision making model and showed that optimal worker-machine assignment can lead to about 20% production cost reduction, while the key performance indicators (KPI) of the U-shaped production line are significantly increased. The sensitivity analysis of influencing factors made it possible to identify the critical factors of this decision making problem, such as the qualification of operators, time of technological and logistics operations, and maintenance policy.