IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v11y2020i5d10.1007_s13198-020-01015-5.html
   My bibliography  Save this article

A resilience engineering-based approach to improving service reliability in maintenance organizations

Author

Listed:
  • Seyed Mohammad Asadzadeh

    (University of Tehran)

  • Hadi Maleki

    (University of Tehran)

  • Mehrab Tanhaeean

    (University of Tehran)

Abstract

Resilience engineering (RE) has introduced new ideas into reliability engineering and safety science and has highlighted new concepts of safe work that could be considered for reliability improvement. The aim of this paper is to put forward an approach within the framework of resilience engineering to service reliability improvement in maintenance organizations. The strategy for reliability improvement is based on mutual learning through collaboration among maintenance departments of a public gas company in 11 districts. The proposed approach first assesses RE in the maintenance departments using a standardized questionnaire. Using a linear regression model, then the relationship between RE and service reliability in the maintenance departments is identified. Service reliability is defined as the probability of undesirable events: non-working valves, gas leaks, unavailability of valves due to coverage by asphalt, and gas flow cut-offs. The pros and cons of departmental collaborative learning in terms of absorbing the RE best practices, managerial or political conflicts, and collaboration costs are discussed. Finally, a linear integer programming is formulated to find the best collaborative connections so that the maintenance departments could find those peers from whom they can benefit most, boost their RE practice, and finally improve their service reliability, while minimizing their costs and possible conflicts.

Suggested Citation

  • Seyed Mohammad Asadzadeh & Hadi Maleki & Mehrab Tanhaeean, 2020. "A resilience engineering-based approach to improving service reliability in maintenance organizations," 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. 11(5), pages 909-922, October.
    • Handle: RePEc:spr:ijsaem:v:11:y:2020:i:5:d:10.1007_s13198-020-01015-5
    DOI: 10.1007/s13198-020-01015-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-020-01015-5
    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/s13198-020-01015-5?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. Hosseini, Seyedmohsen & Barker, Kash & Ramirez-Marquez, Jose E., 2016. "A review of definitions and measures of system resilience," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 47-61.
    2. Masoud Rabbani & Reza Yazdanparast & Mahdi Mobini, 2019. "An algorithm for performance evaluation of resilience engineering culture based on graph theory and matrix approach," 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 228-241, April.
    3. Furniss, Dominic & Back, Jonathan & Blandford, Ann & Hildebrandt, Michael & Broberg, Helena, 2011. "A resilience markers framework for small teams," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 2-10.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Wang, Wei & Maio, Francesco Di & Zio, Enrico, 2017. "Three-loop Monte Carlo simulation approach to Multi-State Physics Modeling for system reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 276-289.
    6. Shirali, Gh.A. & Mohammadfam, I. & Ebrahimipour, V., 2013. "A new method for quantitative assessment of resilience engineering by PCA and NT approach: A case study in a process industry," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 88-94.
    7. Aven, Terje & Zio, Enrico, 2011. "Some considerations on the treatment of uncertainties in risk assessment for practical decision making," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 64-74.
    8. Azadeh, A. & Amalnick, M.S. & Ghaderi, S.F. & Asadzadeh, S.M., 2007. "An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors," Energy Policy, Elsevier, vol. 35(7), pages 3792-3806, July.
    9. Ali Azadeh & Delaram Heydarian & Keivan Nemati & Reza Yazdanparast, 2018. "Performance optimization of unique resilient human resource management system in a coal mine industry," 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. 9(5), pages 1178-1197, October.
    10. Rimkevicius, Sigitas & Kaliatka, Algirdas & Valincius, Mindaugas & Dundulis, Gintautas & Janulionis, Remigijus & Grybenas, Albertas & Zutautaite, Inga, 2012. "Development of approach for reliability assessment of pipeline network systems," Applied Energy, Elsevier, vol. 94(C), pages 22-33.
    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. Karar, Ahmed Noaman & Labib, Ashraf & Jones, Dylan, 2024. "A resilience-based maintenance optimisation framework using multiple criteria and Knapsack methods," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    2. Ahmad Morshedi & Navid Nezafati & Sajjad Shokouhyar, 2024. "Motivational Factors Affecting Knowledge Sharing in Steel Industry Supply Chain: A Mixed Qualitative-Quantitative Method Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 6273-6311, June.
    3. M. Radic & P. Herrmann & P. Haberland & Carla R. Riese, 2022. "Development of a Business Model Resilience Framework for Managers and Strategic Decision-makers," Schmalenbach Journal of Business Research, Springer, vol. 74(4), pages 575-601, 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. Seyed Mohammad Asadzadeh & Hadi Maleki & Mehrab Tanhaeean, 0. "A resilience engineering-based approach to improving service reliability in maintenance organizations," 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. 0, pages 1-14.
    2. Francis, Royce & Bekera, Behailu, 2014. "A metric and frameworks for resilience analysis of engineered and infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 90-103.
    3. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    4. Amro Nasr & Oskar Larsson Ivanov & Ivar Björnsson & Jonas Johansson & Dániel Honfi, 2021. "Towards a Conceptual Framework for Built Infrastructure Design in an Uncertain Climate: Challenges and Research Needs," Sustainability, MDPI, vol. 13(21), pages 1-19, October.
    5. Fernández, David & Pozo, Carlos & Folgado, Rubén & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2018. "Productivity and energy efficiency assessment of existing industrial gases facilities via data envelopment analysis and the Malmquist index," Applied Energy, Elsevier, vol. 212(C), pages 1563-1577.
    6. Nuri Ozgur DOGAN & Can Tansel TUGCU, 2015. "Energy Efficiency in Electricity Production: A Data Envelopment Analysis (DEA) Approach for the G-20 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 246-252.
    7. Azadeh, A. & Ghaderi, S.F. & Nasrollahi, M.R., 2011. "Location optimization of wind plants in Iran by an integrated hierarchical Data Envelopment Analysis," Renewable Energy, Elsevier, vol. 36(5), pages 1621-1631.
    8. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    9. Fukuyama, Hirofumi & Liu, Hui-hui & Song, Yao-yao & Yang, Guo-liang, 2021. "Measuring the capacity utilization of the 48 largest iron and steel enterprises in China," European Journal of Operational Research, Elsevier, vol. 288(2), pages 648-665.
    10. Kenneth Martínez & David Claudio, 2023. "Expanding Fundamental Boundaries between Resilience and Survivability in Systems Engineering: A Literature Review," Sustainability, MDPI, vol. 15(6), pages 1-27, March.
    11. Perroni, Marcos G. & Gouvea da Costa, Sergio E. & Pinheiro de Lima, Edson & Vieira da Silva, Wesley & Tortato, Ubiratã, 2018. "Measuring energy performance: A process based approach," Applied Energy, Elsevier, vol. 222(C), pages 540-553.
    12. Veronese da Silva, Aline & Costa, Marcelo Azevedo & Lopes-Ahn, Ana Lúcia, 2022. "Accounting multiple environmental variables in DEA energy transmission benchmarking modelling: The 2019 Brazilian case," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).
    13. Perroni, Marcos G. & Gouvea da Costa, Sergio E. & Pinheiro de Lima, Edson & Vieira da Silva, Wesley, 2017. "The relationship between enterprise efficiency in resource use and energy efficiency practices adoption," International Journal of Production Economics, Elsevier, vol. 190(C), pages 108-119.
    14. Blancke, Olivier & Tahan, Antoine & Komljenovic, Dragan & Amyot, Normand & Lévesque, Mélanie & Hudon, Claude, 2018. "A holistic multi-failure mode prognosis approach for complex equipment," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 136-151.
    15. Fang, Hong & Wu, Junjie & Zeng, Catherine, 2009. "Comparative study on efficiency performance of listed coal mining companies in China and the US," Energy Policy, Elsevier, vol. 37(12), pages 5140-5148, December.
    16. Blomberg, Jerry & Henriksson, Eva & Lundmark, Robert, 2012. "Energy efficiency and policy in Swedish pulp and paper mills: A data envelopment analysis approach," Energy Policy, Elsevier, vol. 42(C), pages 569-579.
    17. Cui, Qiang & Kuang, Hai-bo & Wu, Chun-you & Li, Ye, 2014. "The changing trend and influencing factors of energy efficiency: The case of nine countries," Energy, Elsevier, vol. 64(C), pages 1026-1034.
    18. Novak, Jeremy & Farr-Wharton, Ben & Brunetto, Yvonne & Shacklock, Kate & Brown, Kerry, 2017. "Safety outcomes for engineering asset management organizations: Old problem with new solutions?," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 67-73.
    19. Mandal, Sabuj Kumar, 2010. "Do undesirable output and environmental regulation matter in energy efficiency analysis? Evidence from Indian Cement Industry," Energy Policy, Elsevier, vol. 38(10), pages 6076-6083, October.
    20. Apostolos Christopoulos & Ioannis Dokas & Sofia Katsimardou & Eleftherios Spyromitros, 2022. "The Malmquist Productivity measure for UK-listed firms in the aftermath of the global financial crisis," Operational Research, Springer, vol. 22(2), pages 1617-1634, April.

    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:11:y:2020:i:5:d:10.1007_s13198-020-01015-5. 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.