Method for Determining Material Demands by Combing Deterministic and Probabilistic Information in Flexible and Changeable Production Systems

In today's dynamic manufacturing environment, flexible and resilient production systems are crucial for coping with constantly changing internal product and production requirements coupled with external market and customer demands. Conventional production systems often lack the capability to adapt to changing requirements due to their fixed structures and technical limitations. To address these challenges, various flexible and changeable production system approaches have been developed in the last years. However, material provision becomes challenging due to increasing degrees of freedom and uncertainty due to arising turbulences, making it difficult to match demand and material provision in terms of time, location, and quantity. This paper presents a method to determine material demands that considers both deterministic and probabilistic information regarding material demand location, quantity, and time. An experimental research approach based on a minimal system was pursued, incorporating simulation experiments covering parameter variation using the Monte Carlo method. The results demonstrate that the developed method successfully determines material demands, enabling flexible and target-size-optimized material provision with potentially arising turbulences.