Supervisory-based capacity allocation control for manufacturing systems

This paper aims at developing supervisory control architecture in order to improve the performance of manufacturing systems. The proposed control architecture is hierarchical. It is composed of basic-level fuzzy logic controllers supervised by a higher level decision-making combining local and global performance indicators to allocate the production capacity. The global performance indicator used in the supervisory level evolves in a tolerance interval defined by the normal operating conditions of the process. When a performance indicator value is outside the predefined tolerance interval, abnormal behaviour occurs. In this case, the supervisor allocates the production capacity or reduces the production throughput according to the aggregated global performance indicators. The simulation results for two applications of manufacturing systems are presented to illustrate the feasibility of the proposed approach.