Karl G. Kempf

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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, threeechelon demand network(More)
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)
The understanding of what constitutes a ‘‘good’’ production schedule is central to the development and evaluation of automated scheduling systems and their implementation in real-world factories. In this paper, we provide a definition of a schedule and discuss potential uses for a schedule within the organization. We then describe a number of different(More)
Model predictive control (MPC) is presented as a robust, flexible decision framework for dynamically managing inventories and satisfying customer demand in demand networks. In this paper, a formulation and the benefits of an MPC-based, control-oriented tactical inventory management system meaningful to the semiconductor industry are presented via two(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)
Model Predictive Control (MPC) is presented as a tactical decision module for supply chain management in semiconductor manufacturing. A representative problem which includes distinguishing features of semiconductor manufacturing supply chains, such as material reconfiguration and stochastic product splits, is examined. Fluid analogies are used to model the(More)