Autonomous recovery of global efficiency based local interaction for flexible transfer system (FTS)

The flexible transfer system (FTS) is a self-organizing manufacturing system composed of autonomous transfer modules, which transfer a pallet loaded with machining parts. In the paper the central issue is the improvement of the performance of the FTS. By learning automata (LA), the FTS can generate a quasi-optimal transfer path by self-organization of a multi-layered strategic vector field corresponding to a task, and can also recover the system performance against sudden environmental change, such as the malfunction of some transfer modules or the change of machining task. However, in the case where the FTS is composed of large number of modules, we find that it may not work sufficiently. We suggest an idea to improve the performance in such case, and verify the effectiveness by numerical simulation