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Smart Maintenance: an empirically grounded conceptualization

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  • Bokrantz, Jon
  • Skoogh, Anders
  • Berlin, Cecilia
  • Wuest, Thorsten
  • Stahre, Johan

Abstract

How do modernized maintenance operations, often referred to as “Smart Maintenance”, impact the performance of manufacturing plants? The inability to answer this question backed by data is a problem for industrial maintenance management, especially in light of the ongoing rapid transition towards an industrial environment with pervasive digital technologies. To this end, this paper, which is the first part of a two-paper series, aims to investigate and answer the question, “What is Smart Maintenance?“. The authors deployed an empirical, inductive research approach to conceptualize Smart Maintenance using focus groups and interviews with more than 110 experts from over 20 different firms. By viewing our original data through the lens of multiple general theories, our findings chart new directions for contemporary and future maintenance research. This paper describes empirical observations and theoretical interpretations cumulating in the first empirically grounded definition of Smart Maintenance and its four underlying dimensions; data-driven decision-making, human capital resource, internal integration, and external integration. In addition, the relationships between the underlying dimensions are specified and the concept structure formally modeled. This study thus achieves concept clarity with respect to Smart Maintenance, thereby making several theoretical and managerial contributions that guide both scholars and practitioners within the field of industrial maintenance management.

Suggested Citation

  • Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Wuest, Thorsten & Stahre, Johan, 2020. "Smart Maintenance: an empirically grounded conceptualization," International Journal of Production Economics, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:proeco:v:223:y:2020:i:c:s0925527319303615
    DOI: 10.1016/j.ijpe.2019.107534
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    2. Theissler, Andreas & Pérez-Velázquez, Judith & Kettelgerdes, Marcel & Elger, Gordon, 2021. "Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Nguyen Bac Nguyen & João Carlos Rosmaninho Menezes, 2021. "The thirty-year evolution of customer-to-customer interaction research: a systematic literature review and research implications," Service Business, Springer;Pan-Pacific Business Association, vol. 15(3), pages 391-444, September.
    4. Pedersen, Tom Ivar & Vatn, Jørn, 2022. "Optimizing a condition-based maintenance policy by taking the preferences of a risk-averse decision maker into account," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    5. Tortorella, Guilherme Luz & Fogliatto, Flavio S. & Cauchick-Miguel, Paulo A. & Kurnia, Sherah & Jurburg, Daniel, 2021. "Integration of Industry 4.0 technologies into Total Productive Maintenance practices," International Journal of Production Economics, Elsevier, vol. 240(C).
    6. Pedersen, Tom Ivar & Liu, Xingheng & Vatn, Jørn, 2023. "Maintenance optimization of a system subject to two-stage degradation, hard failure, and imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    7. Hamzeh Soltanali & Mehdi Khojastehpour & Siamak Kheybari, 2023. "Evaluating the critical success factors for maintenance management in agro-industries using multi-criteria decision-making techniques," Operations Management Research, Springer, vol. 16(2), pages 949-968, June.
    8. Vito Introna & Annalisa Santolamazza, 2024. "Strategic maintenance planning in the digital era: a hybrid approach merging Reliability-Centered Maintenance with digitalization opportunities," Operations Management Research, Springer, vol. 17(4), pages 1397-1420, December.
    9. Ágnes Szukits & Péter Móricz, 2024. "Towards data-driven decision making: the role of analytical culture and centralization efforts," Review of Managerial Science, Springer, vol. 18(10), pages 2849-2887, October.
    10. Colombari, Ruggero & Geuna, Aldo & Helper, Susan & Martins, Raphael & Paolucci, Emilio & Ricci, Riccardo & Seamans, Robert, 2023. "The interplay between data-driven decision-making and digitalization: A firm-level survey of the Italian and U.S. automotive industries," International Journal of Production Economics, Elsevier, vol. 255(C).
    11. Laubengaier, Désirée A. & Cagliano, Raffaella & Canterino, Filomena, 2022. "It Takes Two to Tango: Analyzing the Relationship between Technological and Administrative Process Innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    12. Bokrantz, Jon & Skoogh, Anders, 2023. "Adoption patterns and performance implications of Smart Maintenance," International Journal of Production Economics, Elsevier, vol. 256(C).

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