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Artificial Intelligence in Maintenance

In: Complex System Maintenance Handbook

Author

Listed:
  • Khairy A. H. Kobbacy

    (Salford University)

Abstract

Over the past two decades their has been substantial research and development in operations management including maintenance. Kobbacy et al. (2007) argue that the continous research in these areas implies that solutions were not found to many problems. This was attributed to the fact that many of the solutions proposed were for well-defined problems, that the solutions assumed accurate data were available and that the solutions were too computationally expensive to be practical. Artificial intelligence (AI) was recognised by many researchers as a potentially powerful tool especially when combined with OR techniques to tackle such problems. Indeed, there has been vast interest in the applications of AI in the maintenance area as witnessed by the large number of publications in the area. This chapter reviews the application of AI in maintenance management and planning and introduces the concept of developing intelligent maintenance optimisation system.

Suggested Citation

  • Khairy A. H. Kobbacy, 2008. "Artificial Intelligence in Maintenance," Springer Series in Reliability Engineering, in: Complex System Maintenance Handbook, chapter 9, pages 209-231, Springer.
  • Handle: RePEc:spr:ssrchp:978-1-84800-011-7_9
    DOI: 10.1007/978-1-84800-011-7_9
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    Cited by:

    1. Jacopo Panerati & Nicolas Schwind & Stefan Zeltner & Katsumi Inoue & Giovanni Beltrame, 2018. "Assessing the resilience of stochastic dynamic systems under partial observability," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-21, August.
    2. Jaime Campos, 2016. "Managing the information systems in the industrial domain," Cogent Business & Management, Taylor & Francis Journals, vol. 3(1), pages 1180967-118, December.
    3. Fatemeh Moinian & Hamed Sabouhi & Jafar Hushmand & Ahmad Hallaj & Hiwa Khaledi & Mojtaba Mohammadpour, 2017. "Gas turbine preventive maintenance optimization using genetic algorithm," 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(3), pages 594-601, September.

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