Machine performance and availability prediction through the lifetime

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


    Machine performance, availability and long lifetime play important role in operations and maintenance planning for industrial players e.g. with heavy working machines. Recently, circular economy discussions have even more highlighted the role of the maintenance and lifecycle design from the efficiency and sustainability perspective. [1] The new technologies are considered enablers for circular economy change e.g. additive manufacturing enables advanced solutions for both functional optimization and local manufacturing, furthermore the increased intelligence of the products and the data availability during the whole lifetime enable reliability and predictability of machine performance. The manufacturing companies have a crucial role for implementing these changes into the products and machines they produce. Furthermore, in machinery industry, change from single machines to automated machinery fleets brings new challenges for safety, reliability and maintenance; autonomy in mobile machine applications will increase and operator-assisting technologies will be widely utilized. New energy supply systems in machinery, like hybrid technologies, full electric and fuel cell systems are coming to mobile work machines as well. We concentrate in this paper to the importance of early state concept design, design for maintenance, reliability, availability and safety and how significant advantages in Overall Equipment Effectiveness (OEE) can be gained through hybrid modelling and an increased understanding of the system's behaviour throughout its whole life cycle.
    Original languageEnglish
    Title of host publicationProceedings
    PublisherTampere University of Technology
    ISBN (Print)978-9522-15-4040-0
    Publication statusPublished - 2017
    MoE publication typeA4 Article in a conference publication
    Event2nd Annual SMACC Research Seminar 2017 - Tampere, Finland
    Duration: 7 Nov 20177 Nov 2017
    Conference number: 2


    Seminar2nd Annual SMACC Research Seminar 2017
    Internet address


    • machine performance
    • circular economy
    • overall equipment effectiveness
    • hybrid modelling


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