Approach For Autonomous Control Of Intralogistics Considering Deterministic And Probabilistic Material Demand Information In Flexible Production Systems

In today's dynamic production landscape, flexible and resilient production systems are essential to meet the constant changes in internal product and production requirements as well as external market and customer demands. To meet these challenges, various flexible and resilient production system approaches offer the necessary structural, process-related and technological flexibility and resilience. However, the intralogistics material provision within these complex production systems is challenging due to increasing degrees of freedom and uncertainties caused by emerging turbulence, which has even risen very sharply in recent years due to global instability. This makes it difficult to coordinate material demands and material provision in the production system precisely regarding location and quantity. This paper presents a comprehensive approach for determining the material requirements and autonomously executing the corresponding material provision processes in a complex production system, which considers both deterministic and probabilistic information about the material demand’s location, quantity, and time. Utilizing autonomous control in intralogistics decentralizes complexity management in flexible production systems by transferring decision-making and process execution tasks to the system elements. For the development and verification of the comprehensive approach, an experimental research study was pursued based on a flexible production system, including simulation and practical experiments. Defining the deterministic and probabilistic material demands is based on the Monte Carlo method for carrying out simulation experiments with parameter variation. The autonomously controlled, target size-optimized execution of material provision to fulfil the determined material demands is based on an agent-based modelling and control approach for manual and automated intralogistics transport resources. The study showed that improved logistics performance (throughput time and adherence to schedules) can be achieved in flexible production systems in the event of turbulences by considering deterministic and probabilistic material demand information together with autonomous control of material provision.