Evaluation of Control Approaches for Capacity Adjustment in Job Shop Systems

Abstract

Nowadays, manufacturers increasingly face demand fluctuations while working on a variety of products. To flexibly react to these disturbances, capacity adjustments via flexible working time and staffs are common measures. Within this paper, we focus on a machinery-oriented approach by introducing reconfigurable machine tools into an existing job shop system. As these tools need to be included into the production plan, we tackle the strategic question on how to contemplate hardware with software for a given manufacturing system. To this end, we consider PID as the current standard in capacity control and compare it to two classes of advanced techniques from operator theory and predictive control. While analyzing advantages and disadvantages of these methods, we illustrate differences using operator-based right coprime factorization and model predictive control as representatives of these advanced classes and applying them to a simulated four-workstation job shop system.