Matrix production systems are designed to cope with turbulent market environments, which are usually characterized by unstable product demands and fluctuating product mixes. The modular and flexible structure and control of processes, transport systems, and their interactions enable matrix production systems to handle variability and maintain overall system productivity in these environments. From an energy-oriented perspective, this inherent flexibility provides additional options to reduce energy consumption or peak loads. However, these increasingly complex interactions can also lead to greater sensitivity to external effects. Robust production systems follow design criteria that reduce the effects of these external sources of variability. Hence, this paper introduces a methodology to identify design criteria for robust matrix production systems using well-designed simulation experiments, sensitivity metrics, and data mining methods for large volumes of simulation data. Mutual dependencies between production and energy-oriented system performance are investigated, and target-specific design configurations are outlined. The methodology is demonstrated in a simulation-based industrial case study of a mechanical manufacturing system.
Münnich et al. (Thu,) studied this question.