Optimizing Condition Monitoring of Big Data Systems

David Baglee, Unai Gorostegui, Erkki Jantunen, Jaime Campos, Pankaj Sharma

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


    Industrial communication networks are common in a number of manufacturing organisations. The high availability of these networks is crucial for smooth plant operations. Therefore local and remote diagnostics of these networks is of primary importance in determining issues relating to plant reliability and availability. Condition Monitoring (CM) techniques when connected to a network provide a diagnostic system for remote monitoring of manufacturing equipment. The system monitors the health of the network and the equipment and is therefore able to predict performance. However, this leads to the collection, storage and analyses of large amounts of data, which must provide value. These large data sets are commonly referred to as Big Data. This paper presents a general concept of the use of condition monitoring and big data systems to show how they complement each other to provide valuable data to enhance manufacturing competiveness.
    Original languageEnglish
    Title of host publicationProceedings of the 2017 International Conference on Data Mining
    Subtitle of host publicationDMIN'17
    EditorsHamid R. Arabnia, Robert Stahlbock, Mahmoud Abou-Nasr, Gary M. Weiss
    PublisherCSREA Press
    ISBN (Print)978-1-60132-453-5
    Publication statusPublished - 17 Jul 2017
    MoE publication typeA4 Article in a conference publication
    Event13th International Conference on Data Mining, DMIN'17 - Las Vegas, United States
    Duration: 17 Jul 201720 Jul 2017
    https://csce.ucmss.com/cr/books/2017/ConferenceReport?ConferenceKey=DMI (Full proceedings)


    Conference13th International Conference on Data Mining, DMIN'17
    Abbreviated titleDMIN 2017
    Country/TerritoryUnited States
    CityLas Vegas
    OtherDMIN-17 is a part of the World Congress in Computer Science Computer Engineering & Applied Computing CSCE'17
    Internet address


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