IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v196y2009i3p968-978.html
   My bibliography  Save this article

Sample size determination for production yield estimation with multiple independent process characteristics

Author

Listed:
  • Hsu, Ya-Chen
  • Pearn, W.L.
  • Chuang, Ya-Fei

Abstract

Capability measure for processes yield with single characteristic has been investigated extensively, but is still comparatively neglected for processes with multiple characteristics. Wu and Pearn [Wu, C.W., Pearn, W.L., 2005. Measuring manufacturing capability for couplers and wavelength division multiplexers (WDM). International Journal of Advanced Manufacturing Technology 25(5/6), 533-541] proposed a capability index for multiple characteristics called , which provides an exact measure on process yield for multiple characteristics with each characteristic normally distributed. However, the exact sampling distribution of (multiple characteristics) is analytically intractable. In this paper, we apply the bootstrap method for calculating the lower confidence bounds of the index , and determine the sample size for a specified estimation accuracy. In order to obtain a desired estimation quality assurance, the sample size determination is essential as it provides the accuracy of the lower bound obtained from the bootstrap method. For convenience of applications, we tabulate the sample size required for various designated accuracy for the engineers/practitioners to use. A real-world example from manufacturing process with multiple characteristics is investigated to illustrate the applicability of the proposed approach.

Suggested Citation

  • Hsu, Ya-Chen & Pearn, W.L. & Chuang, Ya-Fei, 2009. "Sample size determination for production yield estimation with multiple independent process characteristics," European Journal of Operational Research, Elsevier, vol. 196(3), pages 968-978, August.
    • Handle: RePEc:eee:ejores:v:196:y:2009:i:3:p:968-978
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(08)00389-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. M. Huang & K. Chen & R. Li, 2005. "Graphical Analysis of Capability of a Process Producing a Product Family," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(5), pages 643-657, October.
    2. W. L. Pearn & YA Ching Cheng, 2007. "Estimating process yield based on Spk for multiple samples," International Journal of Production Research, Taylor & Francis Journals, vol. 45(1), pages 49-64, January.
    3. A. F. Bissell, 1990. "How Reliable is Your Capability Index?," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 39(3), pages 331-340, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Li, Der-Chiang & Lin, Liang-Sian, 2013. "A new approach to assess product lifetime performance for small data sets," European Journal of Operational Research, Elsevier, vol. 230(2), pages 290-298.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nien Fan Zhang, 1998. "Estimating process capability indexes for autocorrelated data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(4), pages 559-574.
    2. Wang, Ching-Hsin & Chen, Kuen-Suan, 2020. "New process yield index of asymmetric tolerances for bootstrap method and six sigma approach," International Journal of Production Economics, Elsevier, vol. 219(C), pages 216-223.
    3. Pearn, W.L. & Wu, Chien-Wei, 2006. "Production quality and yield assurance for processes with multiple independent characteristics," European Journal of Operational Research, Elsevier, vol. 173(2), pages 637-647, September.
    4. Kuen-Suan Chen & Kung-Jeng Wang & Tsang-Chuan Chang, 2017. "A novel approach to deriving the lower confidence limit of indices , , and in assessing process capability," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 4963-4981, September.
    5. Rendao Ye & Tiefeng Ma & Songgui Wang, 2011. "Generalized confidence intervals for the process capability indices in general random effect model with balanced data," Statistical Papers, Springer, vol. 52(1), pages 153-169, February.
    6. Chun-Min Yu & Tsun-Hung Huang & Kuen-Suan Chen & Tsung-Yu Huang, 2022. "Construct Six Sigma DMAIC Improvement Model for Manufacturing Process Quality of Multi-Characteristic Products," Mathematics, MDPI, vol. 10(5), pages 1-13, March.
    7. K. Kurian & Thomas Mathew & G. Sebastian, 2008. "Generalized confidence intervals for process capability indices in the one-way random model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(1), pages 83-92, January.

    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:eee:ejores:v:196:y:2009:i:3:p:968-978. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.