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Lot Sizing to Reduce Capacity Utilization in a Production Process with Defective Items, Process Corrections, and Rework

Author

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  • Hau L. Lee

    (Department of Industrial Engineering and Engineering Management, Stanford University, Stanford, California 94305)

Abstract

This paper deals with the lot sizing problem in which the key features of imperfections in a production process are explicitly modelled. These features include: process shifting to out-of-control states, detection of the out-of-control shifts, corrective actions following the detections, and the fixed setup and variable processing times of reworks. The problem is motivated by the wafer probe operation in semiconductor manufacturing. The key objective that drives the lot sizing decision is to reduce the total processing time on a critical resource. Such an objective is aimed at reducing the congestion level at this resource.

Suggested Citation

  • Hau L. Lee, 1992. "Lot Sizing to Reduce Capacity Utilization in a Production Process with Defective Items, Process Corrections, and Rework," Management Science, INFORMS, vol. 38(9), pages 1314-1328, September.
    • Handle: RePEc:inm:ormnsc:v:38:y:1992:i:9:p:1314-1328
    DOI: 10.1287/mnsc.38.9.1314
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    Citations

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    Cited by:

    1. Jie Ding & Betsy S. Greenberg & Hirofumi Matsuo, 1998. "Repetitive Testing Strategies When the Testing Process Is Imperfect," Management Science, INFORMS, vol. 44(10), pages 1367-1378, October.
    2. Biswajit Sarkar & Mehran Ullah & Seok-Beom Choi, 2019. "Joint Inventory and Pricing Policy for an Online to Offline Closed-Loop Supply Chain Model with Random Defective Rate and Returnable Transport Items," Mathematics, MDPI, vol. 7(6), pages 1-20, June.
    3. Wang, H.S., 2009. "A two-phase ant colony algorithm for multi-echelon defective supply chain network design," European Journal of Operational Research, Elsevier, vol. 192(1), pages 243-252, January.
    4. Ding, Jie & Gong, Linguo, 2008. "The effect of testing equipment shift on optimal decisions in a repetitive testing process," European Journal of Operational Research, Elsevier, vol. 186(1), pages 330-350, April.
    5. Oner, Selma & Bilgic, Taner, 2008. "Economic lot scheduling with uncontrolled co-production," European Journal of Operational Research, Elsevier, vol. 188(3), pages 793-810, August.
    6. K-L Hou, 2005. "Optimal production run length for deteriorating production system with a two-state continuous-time Markovian processes under allowable shortages," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(3), pages 346-350, March.
    7. G C Hadjinicola, 2010. "Manufacturing costs in serial production systems with rework," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 342-351, February.
    8. Cordon, Carlos, 1995. "Quality defaults and work-in-process inventory," European Journal of Operational Research, Elsevier, vol. 80(2), pages 240-251, January.
    9. Wright, CM & Mehrez, A, 1998. "An Overview of Representative Research of the Relationships Between Quality and Inventory," Omega, Elsevier, vol. 26(1), pages 29-47, February.
    10. Sarker, Bhaba R. & Jamal, A.M.M. & Mondal, Sanjay, 2008. "Optimal batch sizing in a multi-stage production system with rework consideration," European Journal of Operational Research, Elsevier, vol. 184(3), pages 915-929, February.
    11. Kaijie Zhu & Rachel Q. Zhang & Fugee Tsung, 2007. "Pushing Quality Improvement Along Supply Chains," Management Science, INFORMS, vol. 53(3), pages 421-436, March.
    12. Yeh, Ruey Huei & Ho, Wen-Tsung & Tseng, Sheng-Tsaing, 2000. "Optimal production run length for products sold with warranty," European Journal of Operational Research, Elsevier, vol. 120(3), pages 575-582, February.
    13. Muhammad Tayyab & Biswajit Sarkar & Bernardo Nugroho Yahya, 2018. "Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand," Mathematics, MDPI, vol. 7(1), pages 1-18, December.
    14. Y H Kang & S S Kim & H J Shin, 2010. "A dispatching algorithm for parallel machines with rework processes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 144-155, January.
    15. Wang, Chih-Hsiung, 2009. "Determining the optimal probing lot size for the wafer probe operation in semiconductor manufacturing," European Journal of Operational Research, Elsevier, vol. 197(1), pages 126-133, August.
    16. Singa Wang Chiu & Liang-Wei You & Tsu-Ming Yeh & Tiffany Chiu, 2020. "The Collective Influence of Component Commonality, Adjustable-Rate, Postponement, and Rework on Multi-Item Manufacturing Decision," Mathematics, MDPI, vol. 8(9), pages 1-18, September.
    17. Flapper, Simme Douwe P. & Teunter, Ruud H., 2004. "Logistic planning of rework with deteriorating work-in-process," International Journal of Production Economics, Elsevier, vol. 88(1), pages 51-59, March.
    18. Barad, M. & Bennett, G., 1996. "Optimal yield improvement in multi-stage manufacturing systems," European Journal of Operational Research, Elsevier, vol. 95(3), pages 549-565, December.
    19. Stephen M. Gilbert & Hena M Bar, 1999. "The value of observing the condition of a deteriorating machine," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(7), pages 790-808, October.
    20. Jinfa Chen & David D. Yao & Shaohui Zheng, 2001. "Optimal Replenishment and Rework with Multiple Unreliable Supply Sources," Operations Research, INFORMS, vol. 49(3), pages 430-443, June.
    21. Gong, Linguo, 2012. "The effect of testing errors on a repetitive testing process," European Journal of Operational Research, Elsevier, vol. 220(1), pages 115-124.
    22. Kim, Chang Hyun & Hong, Yushin, 1997. "An extended EMQ model for a failure prone machine with general lifetime distribution," International Journal of Production Economics, Elsevier, vol. 49(3), pages 215-223, May.

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