This grant provides funding for the development of low cost supercomputers that can be distributed throughout the manufacturing shop floor using reconfigurable computers. A reconfigurable computer contains thousands (100,000) of logic gates on a chip whose interconnections can be instantaneously configured by writing to its internal memory to serve as massively parallel computers in which algorithms can be 'hardwired'. Therefore, a reconfigurable computer maintains the programmability of a conventional software-based computing system, yet enables phenomenal improvements in computing. The shop-floor supercomputer will be used for: (a) Distributed time-scaled simulation algorithms that eliminate complexity and overhead of discrete event simulations; and (b) Continuous distributed control algorithms for scheduling discrete-events that eliminate the computational complexity of combinatorial approaches. An experimental shop-floor supercomputer prototype will be constructed and integrated with an industrial ERP system. Novel architectures using reconfigurable computing and gigabit networks for accelerating distributed time-scaled simulation will be investigated. If successful, in the short term, this will lead to the development of a manufacturing co-processor for industrial ERP systems that addresses computational challenges on the manufacturing shop-floor. Such a chips to enterprise system would utilize the inherently massively parallel /distributed nature of simulation and control algorithms and take advantage of 'hardwiring' capability enabled by reconfigurable computing.
The resulting real-time adaptive time-scaling algorithms would utilize the synergy resulting from combining continuous variable distributed control algorithms and time-scaled distributed simulation. Speed-up and accuracy of simulations would be optimized to effectively utilize raw computing power and raw communication network bandwidth. The shop-floor supercomputer will enable ultra-fast distributed simulations (10,000 x real-time) for feedback control of discrete-event scheduling. The potential long-term impact of this work will be reshaping the future of computing and decision making on the manufacturing shop floor.
