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Knowledge reuse integrating the collaboration from experts in industrial maintenance management

Author

Listed:
  • Paula Andrea Potes Ruiz

    (LGP - Laboratoire Génie de Production - ENIT - Ecole Nationale d'Ingénieurs de Tarbes - Toulouse INP - Institut National Polytechnique (Toulouse) - UT - Université de Toulouse)

  • Bernard Kamsu-Foguem

    (LGP - Laboratoire Génie de Production - ENIT - Ecole Nationale d'Ingénieurs de Tarbes - Toulouse INP - Institut National Polytechnique (Toulouse) - UT - Université de Toulouse)

  • Daniel Noyes

    (LGP - Laboratoire Génie de Production - ENIT - Ecole Nationale d'Ingénieurs de Tarbes - Toulouse INP - Institut National Polytechnique (Toulouse) - UT - Université de Toulouse)

Abstract

Distributed environments, technological evolution, outsourcing market and information technology (IT) are factors that considerably influence current and future industrial maintenance management. Repairing and maintaining the plants and installations requires a better and more sophisticated skill set and continuously updated knowledge. Today, maintenance solutions involve increasing the collaboration of several experts to solve complex problems. These solutions imply changing the requirements and practices for maintenance; thus, conceptual models to support multidisciplinary expert collaboration in decision making are indispensable. The objectives of this work are as follows: (i) knowledge formalization of domain vocabulary to improve the communication and knowledge sharing among a number of experts and technical actors with Conceptual Graphs (CGs) formalism, (ii) multi-expert knowledge management with the Transferable Belief Model (TBM) to support collaborative decision making, and (iii) maintenance problem solving with a variant of the Case-Based Reasoning (CBR) mechanism with a process of solving new problems based on the solutions of similar past problems and integrating the experts' beliefs. The proposed approach is applied for the maintenance management of the illustrative case study.

Suggested Citation

  • Paula Andrea Potes Ruiz & Bernard Kamsu-Foguem & Daniel Noyes, 2013. "Knowledge reuse integrating the collaboration from experts in industrial maintenance management," Post-Print hal-00861829, HAL.
    • Handle: RePEc:hal:journl:hal-00861829
    DOI: 10.1016/j.knosys.2013.06.005
    Note: View the original document on HAL open archive server: https://hal.science/hal-00861829
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    Citations

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    Cited by:

    1. Chao Zhang & Guanghui Zhou & Qi Lu & Fengtian Chang, 2017. "Graph-based knowledge reuse for supporting knowledge-driven decision-making in new product development," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7187-7203, December.
    2. Giulia Bruno & Teresa Taurino & Agostino Villa, 2018. "An approach to support SMEs in manufacturing knowledge organization," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1379-1392, August.
    3. Hicham Jabrouni & Bernard Kamsu-Foguem & Laurent Geneste & Christophe Vaysse, 2013. "Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving," Post-Print hal-03526094, HAL.
    4. Chien-Chang Hsu & Min-Sheng Chen, 2016. "Intelligent maintenance prediction system for LED wafer testing machine," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 335-342, April.
    5. Bernard Kamsu-Foguem & Philippe Clermont & Dieudonné Tchuente & Pierre Tiako & Samuel Fosso Wamba, 2023. "Service Provider Risk Mitigation in Aeronautics Supply Chains," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 615-631, December.
    6. Godé, Cécile & Lebraty, Jean-Fabrice, 2015. "Experience feedback as an enabler of coordination: An aerobatic military team case," Scandinavian Journal of Management, Elsevier, vol. 31(3), pages 424-436.

    More about this item

    Keywords

    Collaborative decision making; Experienced knowledge; Transferable belief model; Case-based reasoning; Maintenance management;
    All these keywords.

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