IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v186y2008i2p652-670.html
   My bibliography  Save this article

Fuzzy inference to assess manufacturing process capability with imprecise data

Author

Listed:
  • Hsu, Bi-Min
  • Shu, Ming-Hung

Abstract

No abstract is available for this item.

Suggested Citation

  • Hsu, Bi-Min & Shu, Ming-Hung, 2008. "Fuzzy inference to assess manufacturing process capability with imprecise data," European Journal of Operational Research, Elsevier, vol. 186(2), pages 652-670, April.
  • Handle: RePEc:eee:ejores:v:186:y:2008:i:2:p:652-670
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(07)00226-3
    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. Corbett, Charles J. & Pan, Jeh-Nan, 2002. "Evaluating environmental performance using statistical process control techniques," European Journal of Operational Research, Elsevier, vol. 139(1), pages 68-83, May.
    2. Lee, Hong Tau, 2001. "Cpk index estimation using fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 129(3), pages 683-688, March.
    3. Pearn, W. L. & Wu, Chien-Wei, 2005. "A Bayesian approach for assessing process precision based on multiple samples," European Journal of Operational Research, Elsevier, vol. 165(3), pages 685-695, September.
    4. Prasad, Sameer & Calis, Ayhan, 1999. "Capability indices for material balance accounting," European Journal of Operational Research, Elsevier, vol. 114(1), pages 93-104, April.
    5. Hong, Dug Hun, 2004. "A note on Cpk index estimation using fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 158(2), pages 529-532, October.
    6. P. Filzmoser & R. Viertl, 2004. "Testing hypotheses with fuzzy data: The fuzzy p-value," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 59(1), pages 21-29, February.
    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. Ramli, Azizul Azhar & Watada, Junzo & Pedrycz, Witold, 2011. "Real-time fuzzy regression analysis: A convex hull approach," European Journal of Operational Research, Elsevier, vol. 210(3), pages 606-617, May.
    2. Iván E. Villalón-Turrubiates & Rogelio López-Herrera & Jorge L. García-Alcaraz & José R. Díaz-Reza & Arturo Soto-Cabral & Iván González-Lazalde & Gerardo Grijalva-Avila & José L. Rodríguez-Álvarez, 2022. "A Non-Invasive Method to Evaluate Fuzzy Process Capability Indices via Coupled Applications of Artificial Neural Networks and the Placket–Burman DOE," Mathematics, MDPI, vol. 10(16), pages 1-27, August.

    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. Wu, Chien-Wei, 2009. "Decision-making in testing process performance with fuzzy data," European Journal of Operational Research, Elsevier, vol. 193(2), pages 499-509, March.
    2. A. Parchami & M. Mashinchi, 2010. "A new generation of process capability indices," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(1), pages 77-89.
    3. Cheng-Che Chen & Chun-Mei Lai & Hsiao-Yu Nien, 2010. "Measuring process capability index C pm with fuzzy data," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(3), pages 529-535, April.
    4. Sotirios Bersimis & Stavros Degiannakis & Dimitrios Georgakellos, 2017. "Real-time monitoring of carbon monoxide using value-at-risk measure and control charting," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 89-108, January.
    5. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    6. Erlantz Allur & Iñaki Heras-Saizarbitoria & Olivier Boiral & Francesco Testa, 2018. "Quality and Environmental Management Linkage: A Review of the Literature," Sustainability, MDPI, vol. 10(11), pages 1-15, November.
    7. Muhammad Aslam, 2022. "Neutrosophic F-Test for Two Counts of Data from the Poisson Distribution with Application in Climatology," Stats, MDPI, vol. 5(3), pages 1-11, August.
    8. Kao, Chiang & Liu, Shiang-Tai, 2003. "A mathematical programming approach to fuzzy efficiency ranking," International Journal of Production Economics, Elsevier, vol. 86(2), pages 145-154, November.
    9. Hong, Dug Hun, 2004. "A note on Cpk index estimation using fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 158(2), pages 529-532, October.
    10. Wu, Chien-Wei, 2008. "Assessing process capability based on Bayesian approach with subsamples," European Journal of Operational Research, Elsevier, vol. 184(1), pages 207-228, January.
    11. Cook, Deborah F. & Zobel, Christopher W. & Wolfe, Mary Leigh, 2006. "Environmental statistical process control using an augmented neural network classification approach," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1631-1642, November.
    12. Jung-Lin Hung & Cheng-Che Chen & Chun-Mei Lai, 2020. "Possibility Measure of Accepting Statistical Hypothesis," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    13. Abbas Parchami & S. Taheri & Mashaallah Mashinchi, 2012. "Testing fuzzy hypotheses based on vague observations: a p-value approach," Statistical Papers, Springer, vol. 53(2), pages 469-484, May.
    14. Kumar Rajaram & Charles J. Corbett, 2002. "Achieving Environmental and Productivity Improvements Through Model-Based Process Redesign," Operations Research, INFORMS, vol. 50(5), pages 751-763, October.
    15. Abbas Parchami & S. Taheri & Mashaallah Mashinchi, 2010. "Fuzzy p-value in testing fuzzy hypotheses with crisp data," Statistical Papers, Springer, vol. 51(1), pages 209-226, January.
    16. Shamsuzzaman, Mohammad & Shamsuzzoha, Ahm & Maged, Ahmed & Haridy, Salah & Bashir, Hamdi & Karim, Azharul, 2021. "Effective monitoring of carbon emissions from industrial sector using statistical process control," Applied Energy, Elsevier, vol. 300(C).
    17. Lubiano, María Asunción & Montenegro, Manuel & Sinova, Beatriz & de la Rosa de Sáa, Sara & Gil, María Ángeles, 2016. "Hypothesis testing for means in connection with fuzzy rating scale-based data: algorithms and applications," European Journal of Operational Research, Elsevier, vol. 251(3), pages 918-929.
    18. Xiaomin Zhao & Jiahui Li & Yang Li, 2022. "Impact of Environmental Tax on Corporate Sustainable Performance: Insights from High-Tech Firms in China," IJERPH, MDPI, vol. 20(1), pages 1-13, December.
    19. Wang, Lei & Xu, Linyu & Song, Huimin, 2011. "Environmental performance evaluation of Beijing's energy use planning," Energy Policy, Elsevier, vol. 39(6), pages 3483-3495, June.
    20. Nataliya Chukhrova & Arne Johannssen, 2020. "Randomized versus non-randomized hypergeometric hypothesis testing with crisp and fuzzy hypotheses," Statistical Papers, Springer, vol. 61(6), pages 2605-2641, December.

    More about this item

    Statistics

    Access and download statistics

    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:186:y:2008:i:2:p:652-670. 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.