A mobile maintenance decision support system

Jaime Campos, Om Prakash, Erkki Jantunen

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    The development is reported of an e-maintenance system, ie a mobile maintenance decision support system based on web and mobile technologies. The problem of the lack of experts to troubleshoot a fault in a machine is a long-standing one. It has led to the application of artificial intelligence and, later, distributed artificial intelligence for machine condition monitoring and diagnosis. Recently, web technology, along with wireless communication, is emerging as a potential tool in maintenance, facilitating acquisition of the desired information by the relevant personnel at any time, wherever they may be. It has been found that with the emergence of the new Information and Communications Technology (ICT) new concepts have started to appear, such as e-manufacturing, e-business and e-maintenance. The paper begins by showing the Web and Mobile architecture and then the ICT tools that are used for communication among the different layers of the system and the client machines. This is followed by a demonstration of the use of the system with a faulty bearing simulated signal. In addition, it is explained that a CMMS, ie a mobile work management system, has been tested, with successful results. Finally, it is shown how a mobile emulator was used to perfect the system for different requirements and how this was then tested on a personal digital assistant (PDA).
    Original languageEnglish
    Pages (from-to)42-48
    Number of pages7
    JournalMaintenance & Asset Management
    Volume23
    Issue number2
    Publication statusPublished - 2008
    MoE publication typeA1 Journal article-refereed

    Keywords

    • condition monitoring
    • condition-based maintenance
    • web application
    • mobile appication
    • mobile device
    • PDA
    • database architecture

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  • Cite this

    Campos, J., Prakash, O., & Jantunen, E. (2008). A mobile maintenance decision support system. Maintenance & Asset Management, 23(2), 42-48.