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In this paper, we develop a linear programming framework for computing a quadratic approximation to the value function, which constitutes the off-line computation of a hierarchical FMS scheduling approach previously developed by us. In contrast to previous work, where relatively crude value functions were used, we develop a quadratic approximation that is a prior fit. We consider the multiple part multiple machine discounted cost case and illustrate the approach via a simulation example in the context of an industrial setting. [ABSTRACT FROM AUTHOR]

In this paper, we describe a flow model of an automated-printed circuit card assembly line at the International Business Machines Corporation (IBM) plant at Tucson, Arizona. We use a simulation based on this model as a test bed to discuss the performance of a hierarchical scheduling policy described in [3]. We compare this with other policies for loading parts into a flexible manufacturing system. We demonstrate that the hierarchical strategy is effective in meeting production requirements (both total volume and balance among part types) while limiting average work-in-process (WIP). This is a consequence of the feedback nature of the policy. Hedging (i.e. building up buffer stock) compensates for machine failures, thus resulting in high production percentages. The work-in-process (WIP) is low, as the policy reduces internal queues by respecting the capacity constraints of the system at every instant. [ABSTRACT FROM AUTHOR]

We build a model to measure and account for the cost of quality. We incorporate the impact of quality on lead time variance and on service reliability and demand. Quality costs are a joint and nonlinear function of various parameters of the manufacturing process. Our model shows that it may not be optimal for quality improvement efforts to target products that have the highest defective levels, largest direct costs or consume the maximum capital resources. A stochastic dynamic programming model is developed to evaluate the optimal trade-offs across prevention and appraisal costs, and the costs of failure. [ABSTRACT FROM AUTHOR]

In this paper, we solve a production planning problem that has a direct bearing on the cost to a facility of vendor quality and reliability. This solution is also an important first step in solving the multi-plant coordination problem. We consider a manufacturing facility with one critical raw material, and one or more products whose demand needs to be met. It is assumed that demand for finished goods and the arrival process for raw material are stochastic. We calculate simultaneously the optimal production level, and the raw material order quantity which minimize the total expected cost subject to capacity and release level constraints. The results obtained by our model (the integrated model) show that the production level should be no larger than the production level obtained by solving the traditional (nonintegrated) models, and that major savings are obtained by solving the integrated model. We are also able to characterize and evaluate the cost of reliable supplies of raw material. In addition we solve the above problem in the presence of capacity constraints. A procedure which allocates capacity to different products is presented. [ABSTRACT FROM AUTHOR]