Decision support and automation for malfunction handling and optimization in a feedback production control system for complex production facilities

Classical tasks of production control are scheduling, the putting through of orders and the pursuance of order progress. Conventional shop floor control systems for the support of these tasks take logistical objectives only insufficiently into consideration. The dynamic manufacturing behaviour and the shifting of objectives over time are represented only inadequately. These problems can be encountered by shop floor control systems with a closed information cycle and a closed loop control structure. Based on this background a methodology is introduced that introduces logistical target-orientation, simulation-based monitoring, and knowledge-based malfunction management as building blocks for a closed loop manufacturing control system. With this approach orders are scheduled and put through in consideration of the target factors: observation of due dates, inventory, lead time and utilization of production resources. Furthermore, the developed mechanisms make it possible to react dynamically to disturbances in the manufacturing system by a situation-adjusted examination of production progress. Reaction to these disturbances will be performed by the production control personnel; this personnel is supported in their choice of reactions by simulation based evaluation of the malfunction handling strategies and by visualization mechanisms that aggregate relevant information from simulation studies and real-life production. Disturbance handling strategies that prove to solve an encountered problem are stored in a knowledge-based system that is used in the automated mode of the system. In this mode of operation the system suggests reactions to disturbances to the control personal or is run fully automated to support unsupervised night or weekend shifts.