IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v35y1989i6p743-756.html
   My bibliography  Save this article

Design of Product Specifications for Multi-Characteristic Inspection

Author

Listed:
  • Kwei Tang

    (Department of Quantitative Business Analysis, Louisiana State University, Baton Rouge, Louisiana 70803)

  • Jen Tang

    (Bell Communications Research, Piscataway, New Jersey 08854)

Abstract

A product often requires inspection on more than one characteristic. The traditional method determines inspection specifications for each characteristic independently. This practice ignores the interactions among characteristics in determining the disposition of an item, and prohibits tradeoffs among the quality of characteristics. In this paper, two multi-characteristic screening (complete inspection) models are proposed with different information processing requirements. In both models, screening specifications are jointly determined by considering all the economic and stochastic factors associated with the characteristics of interest. However, in Model 1, each characteristic has separate screening specifications and the inspection results of conformance (acceptance or rejections) of all the characteristics are used to determine the disposition of an item. In the second model, a joint screening rule based on an aggregation of characteristics is used to allow direct tradeoffs among the quality of characteristics. To implement the second model, the exact measured values of all characteristics of an item have to be recorded and used for a decision on that item. These two models are formulated and the solution procedures are developed. A numerical study is used to compare the cost performance and other plan characteristics of the independently-determined single characteristic models and the two multi-characteristic models.

Suggested Citation

  • Kwei Tang & Jen Tang, 1989. "Design of Product Specifications for Multi-Characteristic Inspection," Management Science, INFORMS, vol. 35(6), pages 743-756, June.
    • Handle: RePEc:inm:ormnsc:v:35:y:1989:i:6:p:743-756
    DOI: 10.1287/mnsc.35.6.743
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.35.6.743
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.35.6.743?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. Qin, Ruwen & Cudney, Elizabeth A. & Hamzic, Zlatan, 2015. "An optimal plan of zero-defect single-sampling by attributes for incoming inspections in assembly lines," European Journal of Operational Research, Elsevier, vol. 246(3), pages 907-915.
    2. Yu, Hong-Fwu & Yu, Wen-Ching, 2007. "An optimal mixed policy of inspection and burn-in and the optimal production quantity," International Journal of Production Economics, Elsevier, vol. 105(2), pages 483-491, February.
    3. Cheong Ng, Wing & Van Hui, Yer, 1997. "Economic design of a complete inspection plan with interactive quality improvement," European Journal of Operational Research, Elsevier, vol. 96(1), pages 122-129, January.
    4. Shin, Sangmun & Kongsuwon, Pauline & Cho, Byung Rae, 2010. "Development of the parametric tolerance modeling and optimization schemes and cost-effective solutions," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1728-1741, December.
    5. Hong, Sung Hoon & Kim, Sang Boo & Kwon, Hyuck Moo & Lee, Min Koo, 1998. "Economic design of screening procedures when the rejected items are reprocessed," European Journal of Operational Research, Elsevier, vol. 108(1), pages 65-73, July.
    6. Liu, Songquan & Moskowitz, Herbert & Plante, Robert & Preckel, Paul V., 2002. "Product and process yield estimation with Gaussian quadrature (GQ) reduction: Improvements over the GQ full factorial approach," European Journal of Operational Research, Elsevier, vol. 140(3), pages 655-669, August.

    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:35:y:1989:i:6:p:743-756. 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.