IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v10y2019i2d10.1007_s13198-018-0754-5.html
   My bibliography  Save this article

Analyzing the productivity of maintenance systems using system dynamics modeling method

Author

Listed:
  • Esmaeil Esmaeili

    (Sharif University of Technology)

  • Hasan Karimian

    (Amirkabir University of Technology)

  • Mohammad Najjartabar Bisheh

    (Kansas State University)

Abstract

Achievement of industries in production and offering products depends on different factors like having an appropriate maintenance system. This issue should be reached through the most appropriate and practical methods. In this study, based on how the external parameters would influence the productivity of a maintenance system the researcher aims at designing a dynamic system model to analyze the productivity of a maintenance system using acquired information from a car device company by determination of the percentage of parameters and indexes and their influence on maintenance system productivity. The proposed model is simulated for a system with parameters of precise value according to fixed and variable maintenance policies which the results are represented. The results of different policies described by using computerized simulation of the prepared model on VENSIM software. The time horizon of the systems can be considered from several years to several decades. This research considered 12 weeks for analyzing the system. This time was specified by consultation with experts in the first session of modeling. In such environment a model of productivity evaluation and operation of maintenance seems required that in this research by analyzing influential factors on maintenance system productivity of a factory and by means of acquired samples, it was possible to measure the ratio of maintenance system operation condition according to the posed indexes and their influences on productivity operation. This situation shows that to the extent that positive indexes in the diagram are higher to the same extent maintenance system productivity of company increases.

Suggested Citation

  • Esmaeil Esmaeili & Hasan Karimian & Mohammad Najjartabar Bisheh, 2019. "Analyzing the productivity of maintenance systems using system dynamics modeling method," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(2), pages 201-211, April.
  • Handle: RePEc:spr:ijsaem:v:10:y:2019:i:2:d:10.1007_s13198-018-0754-5
    DOI: 10.1007/s13198-018-0754-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-018-0754-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13198-018-0754-5?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. Hipkin, I. B. & De Cock, C., 2000. "TQM and BPR: lessons for maintenance management," Omega, Elsevier, vol. 28(3), pages 277-292, June.
    2. Lov Kumar & Mukesh Kumar & Santanu Ku. Rath, 2017. "Maintainability prediction of web service using support vector machine with various kernel methods," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 205-222, June.
    3. Lei Zhang & Yifan Zhou & Chuanhui Huang, 2017. "An approximate hybrid approach to maintenance optimisation for a system with multistate components," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 189-196, March.
    4. John D. Sterman & Nelson P. Repenning & Fred Kofman, 1997. "Unanticipated Side Effects of Successful Quality Programs: Exploring a Paradox of Organizational Improvement," Management Science, INFORMS, vol. 43(4), pages 503-521, April.
    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. Rajesh Saha & Abdullahil Azeem & Kazi Wahadul Hasan & Syed Mithun Ali & Sanjoy Kumar Paul, 2021. "Integrated economic design of quality control and maintenance management: Implications for managing manufacturing process," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(2), pages 263-280, April.

    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. Hazhir Rahmandad & Nelson Repenning, 2016. "Capability erosion dynamics," Strategic Management Journal, Wiley Blackwell, vol. 37(4), pages 649-672, April.
    2. Cäker, Mikael & Siverbo, Sven, 2018. "Effects of performance measurement system inconsistency on managers’ role clarity and well-being," Scandinavian Journal of Management, Elsevier, vol. 34(3), pages 256-266.
    3. Gopesh Anand & John Gray & Enno Siemsen, 2012. "Decay, Shock, and Renewal: Operational Routines and Process Entropy in the Pharmaceutical Industry," Organization Science, INFORMS, vol. 23(6), pages 1700-1716, December.
    4. Sarathkumar Rangarajan & Huai Liu & Hua Wang, 2020. "Web service QoS prediction using improved software source code metrics," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-25, January.
    5. Christina Fang & Daniel Levinthal, 2009. "Near-Term Liability of Exploitation: Exploration and Exploitation in Multistage Problems," Organization Science, INFORMS, vol. 20(3), pages 538-551, June.
    6. Taudes, Alfred & Trcka, Michael & Lukanowicz, Martin, 2002. "Organizational learning in production networks," Journal of Economic Behavior & Organization, Elsevier, vol. 47(2), pages 141-163, February.
    7. He, Yan-Qun & Chan, Lai-Kow & Wu, Ming-Lu, 2007. "Balancing productivity and consumer satisfaction for profitability: Statistical and fuzzy regression analysis," European Journal of Operational Research, Elsevier, vol. 176(1), pages 252-263, January.
    8. Kim, Bowon, 2000. "Coordinating an innovation in supply chain management," European Journal of Operational Research, Elsevier, vol. 123(3), pages 568-584, June.
    9. Suvrat S. Dhanorkar & Enno Siemsen & Kevin W. Linderman, 2018. "Promoting Change from the Outside: Directing Managerial Attention in the Implementation of Environmental Improvements," Management Science, INFORMS, vol. 64(6), pages 2535-2556, June.
    10. Marshall Fisher, 2007. "Strengthening the Empirical Base of Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 9(4), pages 368-382, December.
    11. Torsten Bornemann & Cornelia Hattula & Stefan Hattula, 2020. "Successive product generations: financial implications of industry release rhythm alignment," Journal of the Academy of Marketing Science, Springer, vol. 48(6), pages 1174-1191, November.
    12. Reiner, Gerald, 2005. "Customer-oriented improvement and evaluation of supply chain processes supported by simulation models," International Journal of Production Economics, Elsevier, vol. 96(3), pages 381-395, June.
    13. Felicjan Rydzak & Paul A. Monus, 2018. "Shaping organizational network structure to enable sustainable transformation," System Dynamics Review, System Dynamics Society, vol. 34(1-2), pages 255-283, January.
    14. Oskar P. Roemeling & Martin J. Land & Kees Ahaus & Jannes Slomp & Wouter van den Bijllaardt, 2017. "Impact of lean interventions on time buffer reduction in a hospital setting," International Journal of Production Research, Taylor & Francis Journals, vol. 55(16), pages 4802-4815, August.
    15. Ittner, Christopher D. & Larcker, David F., 2001. "Assessing empirical research in managerial accounting: a value-based management perspective," Journal of Accounting and Economics, Elsevier, vol. 32(1-3), pages 349-410, December.
    16. Desheng Dash Wu & David L. Olson, 2014. "A System Dynamics Modelling of Contagion Effects in Accounts Risk Management," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(4), pages 502-511, July.
    17. Michael S. Dahl, 2011. "Organizational Change and Employee Stress," Management Science, INFORMS, vol. 57(2), pages 240-256, February.
    18. Evanschitzky, Heiner & Wangenheim, Florian v. & Wünderlich, Nancy V., 2012. "Perils of Managing the Service Profit Chain: The Role of Time Lags and Feedback Loops," Journal of Retailing, Elsevier, vol. 88(3), pages 356-366.
    19. Repenning, Nelson P. (Nelson Peter), 1998. "The transition problem in product development," Working papers WP 4036-98., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    20. Miles M Yang & Feifei Yang & Tingru Cui & Ying-Chu Cheng, 2019. "Analysing the dynamics of mental models using causal loop diagrams," Australian Journal of Management, Australian School of Business, vol. 44(3), pages 495-512, August.

    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:spr:ijsaem:v:10:y:2019:i:2:d:10.1007_s13198-018-0754-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.