Evaluation of Strategies for the Coupling of Central Planning and Autonomous Control in Dynamic Job Shop Environments

Abstract

Autonomous control is a promising approach to cope with increasing dynamics in production environments. However, an important issue for the acceptance of autonomous control is the provision of a sufficient planning accuracy, e.g., regarding order sequences or workstation assignments. Therefore, transferring autonomous control into practical application requires the coupling of autonomous control with commonly used central planning methods. This paper introduces coupling strategies with different degrees of planning adherence. The introduced strategies are applied to the example of a job shop environment based on real data. The simulation-based comparison considers performance indicators concerning the logistic performance and planning adherence. Besides varying the level of dynamic influences, the simulation study also analyses the impact of different method combinations onto the coupled methods’ performance.