IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v220y2020ics0925527319302567.html
   My bibliography  Save this article

Distinguishing between common cause variation and special cause variation in a manufacturing system: A simulation of decision making for different types of variation

Author

Listed:
  • Lei, Xue
  • MacKenzie, Cameron A.

Abstract

Controlling variation is an important aspect of quality improvement. Deming distinguishes between common cause variation and special cause variation and argues that both types of variation frequently result from people participating in the process. Confusing common cause and special cause variation can lead to incorrect decisions. This article analyzes the impact of an individual's ability to distinguish between common cause and special cause variation by simulating a manufacturing system with several human operators and a production manager. We use a recognition primed decision (RPD) model to simulate how human operators and the production manager would interpret the variation and make decisions to reduce the variation. A shared mental model with the RPD framework describes the interactions between different operators and the production manager. Results from this simulation demonstrate the importance of distinguishing between common cause and special cause variation, especially when problems occur at bottleneck points in the manufacturing system.

Suggested Citation

  • Lei, Xue & MacKenzie, Cameron A., 2020. "Distinguishing between common cause variation and special cause variation in a manufacturing system: A simulation of decision making for different types of variation," International Journal of Production Economics, Elsevier, vol. 220(C).
  • Handle: RePEc:eee:proeco:v:220:y:2020:i:c:s0925527319302567
    DOI: 10.1016/j.ijpe.2019.07.019
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527319302567
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2019.07.019?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. Du, Shichang & Lv, Jun, 2013. "Minimal Euclidean distance chart based on support vector regression for monitoring mean shifts of auto-correlated processes," International Journal of Production Economics, Elsevier, vol. 141(1), pages 377-387.
    2. W. Edwards Deming, 2000. "The New Economics for Industry, Government, Education, 2nd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262541165, April.
    3. Chen, Yikai & Corr, David J. & Durango-Cohen, Pablo L., 2014. "Analysis of common-cause and special-cause variation in the deterioration of transportation infrastructure: A field application of statistical process control for structural health monitoring," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 96-116.
    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. Youssef Sadraoui & Mohamed Er-ratby & Moulay Saddik Kadiri & Abdessamad Kobi, 2024. "Optimization of Quality Process Control and Preventive Maintenance Strategy: A Case Study," SN Operations Research Forum, Springer, vol. 5(4), pages 1-58, December.

    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. Su, Hung-Chung & Kao, Ta-Wei (Daniel) & Linderman, Kevin, 2020. "Where in the supply chain network does ISO 9001 improve firm productivity?," European Journal of Operational Research, Elsevier, vol. 283(2), pages 530-540.
    2. Maynard, A., 2014. "Contracting for Quality in the NHS," Monographs, Office of Health Economics, number 000073.
    3. Mayara Ramos & Fernando A. Forcellini & Marcelo G. G. Ferreira & Simon Bowen & Peter C. Wright, 2022. "Cyclical experience‐based design: A proposal for engaging stakeholders in a co‐creative model for primary health care service design," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 486-503, January.
    4. Pavel Mates & Tomas Lechner & Pavel Rieger & Jitka Pekna, 2013. "Towards e-Government project assessment: European approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 31(1), pages 103-125.
    5. Erwin B. Quendangan, DBA & Ferdinand C. Somido, PhD & Susana C. Bautista, EdD & Pedrito Jose V. Bermudo, PhD & Antonio D.Yango, PhD & Leomar S. Galicia, PhD, 2018. "Quality Management System’s (QMS) impact on organizational performance of the college academic deans: a basis for continual improvement," Journal of Business & Management (COES&RJ-JBM), , vol. 6(1), pages 84-97, January.
    6. Ketai He & Min Zhang & Ling Zuo & Theyab Alhwiti & Fadel M. Megahed, 2017. "Enhancing the monitoring of 3D scanned manufactured parts through projections and spatiotemporal control charts," Journal of Intelligent Manufacturing, Springer, vol. 28(4), pages 899-911, April.
    7. Ho, Linda Lee & Aparisi, Francisco, 2016. "ATTRIVAR: Optimized control charts to monitor process mean with lower operational cost," International Journal of Production Economics, Elsevier, vol. 182(C), pages 472-483.
    8. Anupam Das & Himangshu Paul & Fredric W. Swierczek & Tritos Laosirihongthong, 2006. "A Measurement Instrument For Tqm Implementation In The Thai Manufacturing Industry," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 361-377.
    9. Vishal Singh Patyal & K. Maddulety, 2015. "Interrelationship between Total Quality Management and Six Sigma: A Review," Global Business Review, International Management Institute, vol. 16(6), pages 1025-1060, December.
    10. Iziy Azamsadat & Sadeghpour Gildeh Bahram & Monabbati Ehsan, 2017. "Comparison Between the Economic-Statistical Design of Double and Triple Sampling X¯\bar{X} Control Charts," Stochastics and Quality Control, De Gruyter, vol. 32(1), pages 49-61, June.
    11. Kang Eng Thye, 2014. "A Good Quality Filing System and its Documentation: The Right Information Determined the Right Knowledge for Decision-Making," Information Management and Business Review, AMH International, vol. 6(5), pages 249-254.
    12. Conan Mukherjee & Ranojoy Basu & Aftab Alam, 2020. "A measure of authorship by publications," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 354-361, April.
    13. Baloyi Dingaan & Khumalo Shuti Steph, 2024. "Experiences of Mathematics Primary School Departmental Heads: Pertinent Challenges and Lessons Learnt," HOLISTICA – Journal of Business and Public Administration, Sciendo, vol. 15(1), pages 33-46.
    14. Pearce, Antony & Pons, Dirk & Neitzert, Thomas, 2018. "Implementing lean—Outcomes from SME case studies," Operations Research Perspectives, Elsevier, vol. 5(C), pages 94-104.
    15. Leoni, Roberto Campos & Costa, Antonio Fernando Branco & Machado, Marcela Aparecida Guerreiro, 2015. "The effect of the autocorrelation on the performance of the T2 chart," European Journal of Operational Research, Elsevier, vol. 247(1), pages 155-165.
    16. Kang Eng Thye, 2011. "Quality Research Framework: Enumerative Study Versus Analytic Study from Deming's Perspective," American Journal of Economics and Business Administration, Science Publications, vol. 3(1), pages 126-131, January.
    17. Xueliang Zhou & Pingyu Jiang, 2017. "Variation source identification for deep hole boring process of cutting-hard workpiece based on multi-source information fusion using evidence theory," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 255-270, February.
    18. Khoo, Michael B.C. & Teoh, W.L. & Castagliola, Philippe & Lee, M.H., 2013. "Optimal designs of the double sampling X¯ chart with estimated parameters," International Journal of Production Economics, Elsevier, vol. 144(1), pages 345-357.
    19. Lixin Shen & Hong Wang & Li Da Xu & Xue Ma & Sohail Chaudhry & Wu He, 2016. "Identity management based on PCA and SVM," Information Systems Frontiers, Springer, vol. 18(4), pages 711-716, August.
    20. Seán Paul Teeling & Jan Dewing & Deborah Baldie, 2021. "A Realist Inquiry to Identify the Contribution of Lean Six Sigma to Person-Centred Care and Cultures," IJERPH, MDPI, vol. 18(19), pages 1-21, October.

    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:220:y:2020:i:c:s0925527319302567. 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.