Service-based condition monitoring for cloud-enabled maintenance operations

David Hästbacka, Erkki Jantunen, Mika Karaila, Laurentiu Barna

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    9 Citations (Scopus)

    Abstract

    Condition based maintenance is regarded as a maintenance strategy that through measured component wear balances availability and accurate operation with necessary maintenance operations. In industrial settings there can be hundreds or thousands of objects to monitor, and systems that are distributed into different networks are seldom compatible. This paper proposes a condition monitoring system based on standardized services operating as parts of a service framework. The solution builds on dynamic service composition as well as standard information models for measurement related data, and supports functionality from sensors to cloud applications. The approach has been applied to industrial processing in mining and it can be claimed to improve interoperability as well as reduce engineering effort when composing functionality supporting maintenance operations.
    Original languageEnglish
    Title of host publicationIndustrial Electronics Society , IECON 2016 - 42nd Annual Conference of the IEEE
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages5289-5295
    ISBN (Electronic)978-1-5090-3474-1
    ISBN (Print)978-1-5090-3475-8
    DOIs
    Publication statusPublished - 22 Dec 2016
    MoE publication typeA4 Article in a conference publication
    Event42nd Annual Conference of the IEEE Industrial Electronics Society - Palazzo dei Congressi, Florence, Italy
    Duration: 23 Oct 201626 Oct 2016
    Conference number: 42

    Conference

    Conference42nd Annual Conference of the IEEE Industrial Electronics Society
    Abbreviated titleIECON 2016
    CountryItaly
    CityFlorence
    Period23/10/1626/10/16

    Keywords

    • condition monitoring
    • monitoring
    • sensors
    • production
    • machinery
    • data models

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