IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v28y1982i4p387-399.html
   My bibliography  Save this article

The Impact of Inspector Fallibility on the Inspection Policy in Serial Production Systems

Author

Listed:
  • Donald P. Ballou

    (State University of New York at Albany)

  • Harold L. Pazer

    (State University of New York at Albany)

Abstract

Appropriate inspection is a significant component of production systems. In this paper a model is developed to determine the optimal placement of inspection stations within n-stage linear production systems. This model accommodates two types of inspector fallibility: "predictable," which implies that the error rates are known and constant, and "erratic," which requires a random variable to describe inspector performance. Cost per good unit accepted by the customer is used as the optimizing criterion. The cost-quality response surface is explored through a sequential sensitivity analysis. Our results indicate that under certain conditions the level of predictable inspector fallibility significantly impacts the number and placement of inspection stations as well as cost per good unit produced. The modeled systems, however, were quite insensitive to the variability of inspector performance. This production-inspection model provides management with information on the optimal number and placement of inspection stations for specific planned or existing serial production systems. It can also be used by management to explore various policy options, such as the cost implications of increasing the quality vs. the quantity of inspection stations. The data required by the model can be obtained at reasonable cost provided management is willing to estimate or determine judgementally certain of the variables.

Suggested Citation

  • Donald P. Ballou & Harold L. Pazer, 1982. "The Impact of Inspector Fallibility on the Inspection Policy in Serial Production Systems," Management Science, INFORMS, vol. 28(4), pages 387-399, April.
    • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:4:p:387-399
    DOI: 10.1287/mnsc.28.4.387
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.28.4.387
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.28.4.387?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. Van Volsem, Sofie & Dullaert, Wout & Van Landeghem, Hendrik, 2007. "An Evolutionary Algorithm and discrete event simulation for optimizing inspection strategies for multi-stage processes," European Journal of Operational Research, Elsevier, vol. 179(3), pages 621-633, June.
    2. Klein, Barbara D., 2001. "Detecting errors in data: clarification of the impact of base rate expectations and incentives," Omega, Elsevier, vol. 29(5), pages 391-404, October.
    3. Donald Ballou & Richard Wang & Harold Pazer & Giri Kumar Tayi, 1998. "Modeling Information Manufacturing Systems to Determine Information Product Quality," Management Science, INFORMS, vol. 44(4), pages 462-484, April.
    4. Hadjinicola, George C. & Soteriou, Andreas C., 2003. "Reducing the cost of defects in multistage production systems: A budget allocation perspective," European Journal of Operational Research, Elsevier, vol. 145(3), pages 621-634, March.
    5. Lee, Jim & Frank Chen, F., 1996. "Inspection sequencing and part scheduling for flexible manufacturing systems," European Journal of Operational Research, Elsevier, vol. 95(2), pages 344-355, December.
    6. Rebello, Ranjit & Agnetis, Alessandro & Mirchandani, Pitu B., 1995. "Specialized inspection problems in serial production systems," European Journal of Operational Research, Elsevier, vol. 80(2), pages 277-296, January.
    7. Paul F. Zantek & Gordon P. Wright & Robert D. Plante, 2002. "Process and Product Improvement in Manufacturing Systems with Correlated Stages," Management Science, INFORMS, vol. 48(5), pages 591-606, May.
    8. Maria R. Ibanez & Michael W. Toffel, 2020. "How Scheduling Can Bias Quality Assessment: Evidence from Food-Safety Inspections," Management Science, INFORMS, vol. 66(6), pages 2396-2416, June.
    9. Douglas G. Bonett & Ronald C. Clute, 1990. "Audit sampling with nonsampling errors of the first type," Contemporary Accounting Research, John Wiley & Sons, vol. 6(2), pages 432-445, March.
    10. 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.
    11. Kim, Hyejeong & Niehm, Linda S., 2009. "The Impact of Website Quality on Information Quality, Value, and Loyalty Intentions in Apparel Retailing," Journal of Interactive Marketing, Elsevier, vol. 23(3), pages 221-233.
    12. Gurnani, Haresh & Drezner, Zvi & Akella, Ram, 1996. "Capacity planning under different inspection strategies," European Journal of Operational Research, Elsevier, vol. 89(2), pages 302-312, March.

    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:28:y:1982:i:4:p:387-399. 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.