Adaptive Production Control in a Modular Assembly System – Towards an Agent-based Approach

Abstract

In industry, individualization leads to a slow replacement of assembly line production with more flexible modular assembly systems. In modular systems, each product can be completed on multiple routes through a grid of modular workstations, where transportation is handled by automated guided vehicles (AGV). In order to benefit from this routing flexibility and to react on disturbances in the system, new robust control approaches are crucial. While optimizing the production flow globally is limited by computing power, this work presents a decentralized control approach that reduces complexity by dividing the problem into sub-problems: A job release agent releases jobs at certain points in time according to the system's inventory level. Each job in the system is linked to a job routing agent regularly choosing the optimal route out of the options given by the product's flexibility. Every modular station is represented by a workstation agent optimizing the workstation's schedule. Lastly, a vehicle agent assigns transports optimally to the AGVs and coordinates them accordingly. An evaluation example emphasized the decentralized approach as a valid way for real-time robust control solutions, where the makespan was about five percent away from the static optimum.