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Dynamic Control of Quality in Production-Inventory Systems

Coordination and Optimization

  • Textbook
  • © 2002

Overview

Authors:
  1. David D. Yao

    1. Department of Operations Research and Industrial Engineering, Columbia University, New York, USA

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  2. Shaohui Zheng

    1. Department of Information and Systems Management, Hong Kong University of Science and Technology, Kowloon, Hong Kong

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    You can also search for this author in PubMed   Google Scholar

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-ix
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  2. Introduction

    • David D. Yao, Shaohui Zheng
    Pages 1-4

  3. Stochastic Monotonicity, Convexity and Submodularity

    • David D. Yao, Shaohui Zheng
    Pages 5-17

  4. Quality Control for Products with Warranty

    • David D. Yao, Shaohui Zheng
    Pages 19-36

  5. Process Control in Batch Production

    • David D. Yao, Shaohui Zheng
    Pages 37-63

  6. Coordinated Production-Inspection in a Tandem System

    • David D. Yao, Shaohui Zheng
    Pages 65-87

  7. Sequential Inspection Under Capacity Constraints

    • David D. Yao, Shaohui Zheng
    Pages 89-107

  8. Coordination of Interstage Inspections

    • David D. Yao, Shaohui Zheng
    Pages 109-137

  9. Optimal Inspection in an Assembly System

    • David D. Yao, Shaohui Zheng
    Pages 139-157

  10. Coordinated Replenishment and Rework with Unreliable Supply Sources

    • David D. Yao, Shaohui Zheng
    Pages 159-188

  11. Inventory Control with Substitution

    • David D. Yao, Shaohui Zheng
    Pages 189-205

  12. Back Matter

    Pages 207-218
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Keywords

About this book

Quality control is a scientific means for conducting observations, tests, and inspections and thereby making decisions that improve the perfomance of industrial processes. This book develops a set of dynamic approaches characterized by coordination. In practice, quality control problems almost never exist in isolation. The basic methodology underlying the studies is Markov decision programming. The book can be used as a graduate text for a new course on statistical process control, or as a reference for researchers and practitioners in mathematics, operations research and operations management, quality control, production planning, and logistics.

Authors and Affiliations

  • Department of Operations Research and Industrial Engineering, Columbia University, New York, USA

    David D. Yao

  • Department of Information and Systems Management, Hong Kong University of Science and Technology, Kowloon, Hong Kong

    Shaohui Zheng

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