Adaptive Production Control in a Modular Assembly System Based on Partial Look-Ahead Scheduling

Abstract

An increase in the number of product variants drives the automotive industry slowly to replace assembly lines with more flexible modular production systems. In a modular system, every product variant seeks its route through the modular stations depending on the needed operations. Automated guided vehicles handle the transport of materials. To utilize these routing flexibility advantages of modular assembly systems and to make the necessary decisions in the system, new control approaches are necessary. Trying to optimize the production flow globally is complex and therefore limited by computing power. This work presents a new approach that reduces complexity by using partial schedules. The algorithm concept is as follows: it regularly reads the current production status, optimizes the system globally by looking ahead for a certain period of time and decides by concluding an optimal partial schedule for the modular production system. The optimization is done by a genetic algorithm. For evaluation purposes, a modular assembly system for electric drives from the German automotive industry is used. In conclusion, the presented approach fully utilizes the flexibility given by the evaluation example, while reducing the complexity of the production control problem. Though, further investigations are necessary.