| This study presents the design, development, and implementation of an integrated control framework for discrete event systems. The framework provides a real-time control model with limited look-ahead capability for flexible manufacturing systems. Control goals and policies are modeled and characterized by a fuzzy rule base, which is integrated with the control model, in order to effectively handle qualitative and quantitative performance measures observed in a manufacturing system.; The framework consists of a finite state machine generator and a controller. The generator model is equipped with an output function and output sets. The controller model has a four-stage decision-making structure supported with a fuzzy rule base. The controller model monitors performance measures of the manufacturing system and reacts according to the changes in the system states in order to keep the performance measures at desired levels.; The integrated framework has been implemented on a software platform that includes Visual Basic™, Microsoft Access™, and ARENA™ simulation modules in order to validate its effectiveness. The performance of the framework has been tested on a hypothetical flexible manufacturing system in a simulation environment. The simulation results indicate that control goals and policies, represented in the fuzzy rule base, are effectively employed online in order to achieve desired system-level performance measures within a reasonable computation time. The performance of the manufacturing system varies, based on the selected steps of look-ahead horizons. The simulation study also shows that the framework can easily be reconfigured by modifying the fuzzy rule base and setting different steps of look-ahead horizons. |
