Product and process reconfiguration based on intelligent agents

Many work is in progress for sustaining the global environment, reducing wasted products, decreasing Lead Times and Work In Process (WIP), in order to improve acceptability, effectiveness and service of modem production systems. Main problem comes from this structural complexity. To improve the performance of a Production System, a tool has been developed. It is called Virtual Factory Dynamics Configuration System (VFDCS); it is intended to implement new concepts relevant to Supply Chain Management (SCM) and, Demand Flow Technology (DFT). It is based on inverse approaches in the area of simulation and scheduling and also uses simple methods and rules. Its implementation requires multi-agent systems and focused on interactions existing between the resources. Here, we focus on the implementation of intelligent agents at product and process level. They integrate quantitative and cognitive data-processing, associated with learning capabilities these agents are able to define the rights coupling, to evaluate these assignments and to adjust product and process parameters, thus to perform automatic reconfiguration of a production system. Improvements works are still in progress to integrate such upgrades and enhancements in the next generation of production systems.