IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v45y2014i10p2042-2054.html
   My bibliography  Save this article

Product and process parameters determination for quality and cost

Author

Listed:
  • Angus Jeang
  • Yang-Kuei Lin

Abstract

The purpose of this study is to conduct a concurrent product and process parameters determination for further cost reduction and quality enhancement. The process design-related parameters, such as process mean, process tolerance and product design-related parameters, such as product tolerance, are considered simultaneously in the proposed approach. To reflect the response from these three key controllable characteristics: process mean, process tolerance and product tolerance, the key measurement score, which is the sum of the mean cost, tolerance cost, quality loss and failure cost, is used to evaluate the present model. Two examples are provided for demonstrating the application of single and multiple quality characteristics.

Suggested Citation

  • Angus Jeang & Yang-Kuei Lin, 2014. "Product and process parameters determination for quality and cost," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(10), pages 2042-2054, October.
    • Handle: RePEc:taf:tsysxx:v:45:y:2014:i:10:p:2042-2054
    DOI: 10.1080/00207721.2012.760761
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2012.760761
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2012.760761?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
    ---><---

    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. Yu-Chung Tsao, 2013. "Combined production-maintenance decisions in situations with process deterioration," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(9), pages 1692-1700.
    2. Chen, Chung-Ho & Lai, Min-Tsai, 2007. "Determining the optimum process mean based on quadratic quality loss function and rectifying inspection plan," European Journal of Operational Research, Elsevier, vol. 182(2), pages 755-763, October.
    3. Jianjun Shi & Shiyu Zhou, 2009. "Quality control and improvement for multistage systems: A survey," IISE Transactions, Taylor & Francis Journals, vol. 41(9), pages 744-753.
    Full references (including those not matched with items on IDEAS)

    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. Chongyang Liu & Ryan Loxton & Kok Teo, 2014. "Optimal parameter selection for nonlinear multistage systems with time-delays," Computational Optimization and Applications, Springer, vol. 59(1), pages 285-306, October.
    2. Xiaoqin Wen & Chenhanzhi Wang, 2022. "Optimal-Quality Choice and Committed Delivery Time in Build-To-Order Supply Chain," Sustainability, MDPI, vol. 14(18), pages 1-20, September.
    3. Darwish, M.A. & Abdulmalek, F. & Alkhedher, M., 2013. "Optimal selection of process mean for a stochastic inventory model," European Journal of Operational Research, Elsevier, vol. 226(3), pages 481-490.
    4. Jinho Kim & Myong K. Jeong & Elsayed A. Elsayed, 2017. "Monitoring multistage processes with autocorrelated observations," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2385-2396, April.
    5. Dodd, Christopher S. & Scanlan, James & Wiseall, Steve, 2021. "Generalising optimal mean setting for any number and combination of serial and parallel manufacturing operations," International Journal of Production Economics, Elsevier, vol. 236(C).
    6. Lu, Biao & Chen, Zhen & Zhao, Xufeng, 2021. "Data-driven dynamic predictive maintenance for a manufacturing system with quality deterioration and online sensors," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    7. Chung-Ho Chen, 2010. "A note on some modified Pulak and Al-Sultan's model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(3), pages 461-472.
    8. Bera, Sasadhar & Mukherjee, Indrajit, 2016. "A multistage and multiple response optimization approach for serial manufacturing system," European Journal of Operational Research, Elsevier, vol. 248(2), pages 444-452.
    9. Lin, Zu-Liang & Huang, Yeu-Shiang & Fang, Chih-Chiang, 2015. "Non-periodic preventive maintenance with reliability thresholds for complex repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 145-156.
    10. Kenneth J. Klassen & Reena Yoogalingam, 2019. "Appointment scheduling in multi-stage outpatient clinics," Health Care Management Science, Springer, vol. 22(2), pages 229-244, June.
    11. Chen-Fu Chien & Chiao-Wen Liu & Shih-Chung Chuang, 2017. "Analysing semiconductor manufacturing big data for root cause detection of excursion for yield enhancement," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5095-5107, September.
    12. Wei, Shuaichong & Nourelfath, Mustapha & Nahas, Nabil, 2023. "Analysis of a production line subject to degradation and preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    13. Liu Yumin & Zhou Haofei, 2014. "MSVM Recognition Model for Dynamic Process Abnormal Pattern Based on Multi-Kernel Functions," Journal of Systems Science and Information, De Gruyter, vol. 2(5), pages 473-480, October.

    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:taf:tsysxx:v:45:y:2014:i:10:p:2042-2054. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.