IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v43y1997i9p1214-1228.html
   My bibliography  Save this article

Opportunities for Improved Statistical Process Control

Author

Listed:
  • Evan L. Porteus

    (Graduate School of Business, Stanford University, Stanford, California 94305)

  • Alexandar Angelus

    (Graduate School of Business, Stanford University, Stanford, California 94305)

Abstract

Our Bayesian dynamic programming model builds on existing models to account for inspection delay, choice of keeping production going during inspection and/or restoration, and lot sizing. We focus on describing how dynamic statistical process control (DSPC) rules can improve on traditional, static ones. We explore numerical examples and identify nine opportunities for improvement. Some of these ideas are well known and strongly supported in the literature. Other ideas may be less well understood. Our list includes the following: Cancel some of the inspections called for by an (economically) optimal static rule when starting in control (such as at the beginning of a production run and following a restoration). Inspect more frequently than called for by an optimal static rule once inspections begin, and inspect even more frequently than that when negative evidence is accumulated. Utilize evidence from previous inspections to justify either restoration or another inspection. Cancel inspections and hesitate to restore the process at the end of a production run. Consider using scheduled restoration, in which restoration is carried out regardless of the results of any inspections. Implementation, limitations, and extensions are addressed.

Suggested Citation

  • Evan L. Porteus & Alexandar Angelus, 1997. "Opportunities for Improved Statistical Process Control," Management Science, INFORMS, vol. 43(9), pages 1214-1228, September.
    • Handle: RePEc:inm:ormnsc:v:43:y:1997:i:9:p:1214-1228
    DOI: 10.1287/mnsc.43.9.1214
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.43.9.1214
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.43.9.1214?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luo Hua & Wu Zhang, 2002. "Optimal np Control Charts with Variable Sample Sizes or Variable Sampling Intervals," Stochastics and Quality Control, De Gruyter, vol. 17(1), pages 39-61, January.
    2. Viliam Makis, 2008. "Multivariate Bayesian Control Chart," Operations Research, INFORMS, vol. 56(2), pages 487-496, April.
    3. Linderman, Kevin & McKone-Sweet, Kathleen E. & Anderson, John C., 2005. "An integrated systems approach to process control and maintenance," European Journal of Operational Research, Elsevier, vol. 164(2), pages 324-340, July.
    4. Tagaras, George, 2017. "New indices for the evaluation of the statistical properties of Bayesian x¯ control charts for short runsAuthor-Name: Nikolaidis, Yiannis," European Journal of Operational Research, Elsevier, vol. 259(1), pages 280-292.
    5. Makis, Viliam, 2009. "Multivariate Bayesian process control for a finite production run," European Journal of Operational Research, Elsevier, vol. 194(3), pages 795-806, May.
    6. Kulkarni, Shailesh S., 2008. "Loss-based quality costs and inventory planning: General models and insights," European Journal of Operational Research, Elsevier, vol. 188(2), pages 428-449, July.
    7. Shoshana Anily & Abraham Grosfeld-Nir, 2006. "An Optimal Lot-Sizing and Offline Inspection Policy in the Case of Nonrigid Demand," Operations Research, INFORMS, vol. 54(2), pages 311-323, April.
    8. Nenes, George & Tagaras, George, 2007. "The economically designed two-sided Bayesian control chart," European Journal of Operational Research, Elsevier, vol. 183(1), pages 263-277, November.
    9. Abraham Grosfeld‐Nir & Eyal Cohen & Yigal Gerchak, 2007. "Production to order and off‐line inspection when the production process is partially observable," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(8), pages 845-858, December.
    10. Erica L. Plambeck & Terry A. Taylor, 2019. "Testing by Competitors in Enforcement of Product Standards," Management Science, INFORMS, vol. 65(4), pages 1735-1751, April.
    11. Abraham Grosfeld-Nir & Yigal Gerchak & Qi-Ming He, 2000. "Manufacturing to Order with Random Yield and Costly Inspection," Operations Research, INFORMS, vol. 48(5), pages 761-767, October.
    12. Diwakar Gupta & William L. Cooper, 2005. "Stochastic Comparisons in Production Yield Management," Operations Research, INFORMS, vol. 53(2), pages 377-384, April.
    13. Jue Wang & Chi-Guhn Lee, 2015. "Multistate Bayesian Control Chart Over a Finite Horizon," Operations Research, INFORMS, vol. 63(4), pages 949-964, August.
    14. George Tagaras & Yiannis Nikolaidis, 2002. "Comparing the Effectiveness of Various Bayesian X̄ Control Charts," Operations Research, INFORMS, vol. 50(5), pages 878-888, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:43:y:1997:i:9:p:1214-1228. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.