| This research explores the use of model-based knowledge for real-time production planning and control in a CIM system. A two-level hierarchical control system generates adaptive production trajectories using real-time information. The knowledge-based system monitors the production status, reacts to unplanned events, and performs replanning. The approach is demonstrated over a simulated cell for batch manufacturing with several workstations and material handling devices. Results show that production goals are met with low variability and the system adapts well to temporary losses in capacity. Dynamic capacity allocation and dispatching achieve high equipment utilization. An adaptive routing algorithm, using real-time information about the traffic status, achieves low transportation delays. The shell designed for the experiments allows simple integration of heuristic and procedural knowledge for control of dynamic systems, and permits validation of the knowledge base. |
