Control Policy for a Manufacturing System with Random Yield and Rework

L. Gong and Hirofumi Matsuo
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L. Gong: Louisiana State University

Journal of Optimization Theory and Applications, 1997, vol. 95, issue 1, No 7, 149-175

Abstract: Abstract We develop a production policy that controls work-in-process (WIP) levels and satisfies demand in a multistage manufacturing system with significant uncertainty in yield, rework, and demand. The problem addressed in this paper is more general than those in the literature in three aspects: (i) multiple products are processed at multiple workstations, and the capacity of each workstation is limited and shared by multiple operations; (ii) the behavior of a production policy is investigated over an infinite-time horizon, and thus the system stability can be evaluated; (iii) the representation of yield and rework uncertainty is generalized. Generalizing both the system structure and the nature of uncertainty requires a new mathematical development in the theory of infinite-horizon stochastic dynamic programming. The theoretical contributions of this paper are the existence proofs of the optimal stationary control for a stochastic dynamic programming problem and the finite covariances of WIP and production levels under the general expression of uncertainty. We develop a simple and explicit sufficient condition that guarantees the existence of both the optimal stationary control and the system stability. We describe how a production policy can be constructed for the manufacturing system based on the propositions derived.

Keywords: Infinite-horizon stochastic dynamic programming; optimal stationary control; system stability; chance constrained programming; production policy under random yield (search for similar items in EconPapers)
Date: 1997
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DOI: 10.1023/A:1022639529617

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