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High-volume, multistage continuous production flow through a re-entrant factory is modeled through a conservation law for a continuous-density variable on a continuous-production line augmented by a state equation for the speed of the production along the production line. The resulting nonlinear, nonlocal hyperbolic conservation law allows fast and accurate(More)
Model Predictive Control (MPC) is shown to provide a robust, flexible framework to stabilize inventories yet still meet customer demand with minimal safety stock. The translation of available information in the supply chain problem into MPC variables is demonstrated with a two-node supply chain example. A six-node, two-product, three-echelon demand network(More)
Based on the experience in manufacturing production scheduling problems which the AI community has amassed over the last ten years, a workshop was held to provide a forum for discussion of the issues encountered in the design of AI-based scheduling systems. Several topics were addressed including : the relative virtues of expert system , deep method, and(More)
Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network systems. Detailed simulation of physical processes provides information for its controller to account for (expected) stochasticity present in the manufacturing processes. In turn, the controller can(More)
Pittsburgh. His research interests include constraint-based planning and scheduling , integration of predictive and reactive decision-making, distributed problem solving, temporal reasoning, machine learning, and knowledge-based production management. He has been a principal architect of several knowledge-based scheduling systems for complex manufacturing(More)