A connectionist network for some elements of real-time planning and control in a manufacturing system
Connectionism is an approach currently being used in the field of cognitive science to investigate intelligence. Connectionist models are based upon the information processing properties of neurons in the brain and consist of very many, simple, interconnected processing elements which operate upon simple signals in parallel. The main objective of the work reported here is to show that connectionism may be applied to areas other than cognitive science. A simulation program has been implemented in which a connectionist network performs the real-time planning and control activities required to supervise the movement and processing of parts in a manufacturing system. The concurrency of connectionism is exploited in such a way that production of a part type may be characterised as “parallel”, where many machine tools are specified to perform each one of the operations required to transform raw material into finished product. The connectionist network is able to control all of these machines simultaneously and in real-time so that many parts can be at any stage of completion in a production facility. The precise routing of a part through the production facility is not specified in advance. Instead, the machine to which a part is scheduled next and the route by which it reaches this machine are decided when the part completes its current operation. These decisions are based upon the availabilities of machines at the time the decisions are made. The connectionist network is able to make these decisions, for every part in the production facility, in negligible time. The benefit of this approach is shown when the breakdown of machines is simulated. The network is able to react autonomously to breakdown by scheduling and routing parts around the affected machine. The necessary computations can be performed in real-time so that breakdown does not cause the manufacturing system to halt while production is re-planned.