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Control Policy for a Manufacturing System with Random Yield and Rework

Author

Listed:
  • L. Gong

    (Louisiana State University)

  • H. Matsuo

    (University of Texas at Austin)

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.

Suggested Citation

  • L. Gong & H. Matsuo, 1997. "Control Policy for a Manufacturing System with Random Yield and Rework," Journal of Optimization Theory and Applications, Springer, vol. 95(1), pages 149-175, October.
    • Handle: RePEc:spr:joptap:v:95:y:1997:i:1:d:10.1023_a:1022639529617
    DOI: 10.1023/A:1022639529617
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    References listed on IDEAS

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    Cited by:

    1. Bordoloi, Sanjeev & Guerrero, Hector H., 2008. "Design for control: A new perspective on process and product innovation," International Journal of Production Economics, Elsevier, vol. 113(1), pages 346-358, May.
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    3. Sanjeev Bordoloi, 2006. "A control rule for recruitment planning in engineering consultancy," Journal of Productivity Analysis, Springer, vol. 26(2), pages 147-163, October.
    4. Bordoloi, Sanjeev K. & Matsuo, Hirofumi, 2001. "Human resource planning in knowledge-intensive operations: A model for learning with stochastic turnover," European Journal of Operational Research, Elsevier, vol. 130(1), pages 169-189, April.

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