IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v188y2017icp156-166.html
   My bibliography  Save this article

Cost of quality: Evaluating cost-quality trade-offs for inspection strategies of manufacturing processes

Author

Listed:
  • Farooq, Muhammad Arsalan
  • Kirchain, Randolph
  • Novoa, Henriqueta
  • Araujo, Antonio

Abstract

Cost-quality trade-offs are required when manufacturing industries seek to minimize cost and maximize product quality or reliability. We report a challenging cost-quality tradeoff problem for a consumer goods industry where both cost and quality are modeled together. First we present a 10-step systems engineering methodology for quality improvement of manufacturing systems and comprehensively discuss the cost of quality step. The methodology investigates in detail inspection strategies of the manufacturing systems by exploring four alternative strategies. Key elements in this investigation consists of modeling the appraisal costs that involve costs to detect a non-conformed unit through inspection or testing, and failure costs that involve costs of rework, scrap, warranty claims and loss of goodwill and sales. Among the main findings of the research is that optimum inspection strategy can be achieved by modeling the cost savings from each strategy and plotting against non-conforming rates shipped to the customer and additional external failure premium.

Suggested Citation

  • Farooq, Muhammad Arsalan & Kirchain, Randolph & Novoa, Henriqueta & Araujo, Antonio, 2017. "Cost of quality: Evaluating cost-quality trade-offs for inspection strategies of manufacturing processes," International Journal of Production Economics, Elsevier, vol. 188(C), pages 156-166.
    • Handle: RePEc:eee:proeco:v:188:y:2017:i:c:p:156-166
    DOI: 10.1016/j.ijpe.2017.03.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527317301135
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2017.03.019?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. Wu, Chien-Wei, 2012. "An efficient inspection scheme for variables based on Taguchi capability index," European Journal of Operational Research, Elsevier, vol. 223(1), pages 116-122.
    2. Chen, Jianwei & Li, Kim-Hung & Lam, Yeh, 2007. "Bayesian single and double variable sampling plans for the Weibull distribution with censoring," European Journal of Operational Research, Elsevier, vol. 177(2), pages 1062-1073, March.
    3. Pursglove, A. B. & Dale, B. G., 1995. "Developing a quality costing system: Key features and outcomes," Omega, Elsevier, vol. 23(5), pages 567-575, October.
    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. Choi, Yunsik & Delise, Lisa A. & Lee, Brandon W. & Neely, Jerry, 2021. "Effective staffing of projects for reconciling conflict between cost efficiency and quality," International Journal of Production Economics, Elsevier, vol. 234(C).
    2. Qian, Cheng & Anderson, Edward, 2020. "Buyer’s optimal information revelation strategy in procurement auctions," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1011-1025.
    3. Hauck, Zsuzsanna & Rabta, Boualem & Reiner, Gerald, 2021. "Joint quality and pricing decisions in lot sizing models with defective items," International Journal of Production Economics, Elsevier, vol. 241(C).

    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. Chien-Wei Wu & Zih-Huei Wang, 2017. "Developing a variables multiple dependent state sampling plan with simultaneous consideration of process yield and quality loss," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2351-2364, April.
    2. Wu, Chien-Wei & Aslam, Muhammad & Jun, Chi-Hyuck, 2012. "Variables sampling inspection scheme for resubmitted lots based on the process capability index Cpk," European Journal of Operational Research, Elsevier, vol. 217(3), pages 560-566.
    3. Fernández, Arturo J. & Pérez-González, Carlos J. & Aslam, Muhammad & Jun, Chi-Hyuck, 2011. "Design of progressively censored group sampling plans for Weibull distributions: An optimization problem," European Journal of Operational Research, Elsevier, vol. 211(3), pages 525-532, June.
    4. Fernández, Arturo J., 2017. "Economic lot sampling inspection from defect counts with minimum conditional value-at-risk," European Journal of Operational Research, Elsevier, vol. 258(2), pages 573-580.
    5. CHEN, Piao & YE, Zhi-Sheng, 2018. "A systematic look at the gamma process capability indices," European Journal of Operational Research, Elsevier, vol. 265(2), pages 589-597.
    6. Amy H. I. Lee & Chien-Wei Wu & Yen-Wen Chen, 2016. "A modified variables repetitive group sampling plan with the consideration of preceding lots information," Annals of Operations Research, Springer, vol. 238(1), pages 355-373, March.
    7. Pérez-González, Carlos J. & Fernández, Arturo J. & Kohansal, Akram, 2020. "Efficient truncated repetitive lot inspection using Poisson defect counts and prior information," European Journal of Operational Research, Elsevier, vol. 287(3), pages 964-974.
    8. Adcock, C J & Meade, N, 2017. "Using parametric classification trees for model selection with applications to financial risk management," European Journal of Operational Research, Elsevier, vol. 259(2), pages 746-765.
    9. Fernández, Arturo J., 2015. "Optimum attributes component test plans for k-out-of-n:F Weibull systems using prior information," European Journal of Operational Research, Elsevier, vol. 240(3), pages 688-696.
    10. Zu‐Liang Lin & Yeu‐Shiang Huang, 2010. "Nonperiodic preventive maintenance for repairable systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(7), pages 615-625, October.
    11. Amy Lee & Chien-Wei Wu & Yen-Wen Chen, 2016. "A modified variables repetitive group sampling plan with the consideration of preceding lots information," Annals of Operations Research, Springer, vol. 238(1), pages 355-373, March.
    12. Kiran Prajapat & Arnab Koley & Sharmishtha Mitra & Debasis Kundu, 2023. "An Optimal Bayesian Sampling Plan for Two-Parameter Exponential Distribution Under Type-I Hybrid Censoring," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 512-539, February.
    13. Kuen-Suan Chen & Hsi-Tien Chen & Tsang-Chuan Chang, 2017. "The construction and application of Six Sigma quality indices," International Journal of Production Research, Taylor & Francis Journals, vol. 55(8), pages 2365-2384, April.
    14. Shih-Wen Liu & Chien-Wei Wu, 2016. "A quick switching sampling system by variables for controlling lot fraction nonconforming," International Journal of Production Research, Taylor & Francis Journals, vol. 54(6), pages 1839-1849, March.
    15. Fernández, Arturo J. & Correa-Álvarez, Cristian D. & Pericchi, Luis R., 2020. "Balancing producer and consumer risks in optimal attribute testing: A unified Bayesian/Frequentist design," European Journal of Operational Research, Elsevier, vol. 286(2), pages 576-587.
    16. Lee, Amy H.I. & Wu, Chien-Wei & Wang, To-Cheng & Kuo, Ming-Han, 2024. "Construction of acceptance sampling schemes for exponential lifetime products with progressive type II right censoring," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    17. Maram Salem & Zeinab Amin & Moshira Ismail, 2020. "Progressively Censored Reliability Sampling Plans Based on Mean Product Lifetime," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(1), pages 1-33, May.

    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:proeco:v:188:y:2017:i:c:p:156-166. 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/ijpe .

    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.