From measurements to knowledge: Online quality monitoring and smart manufacturing

Satu Tamminen, Henna Tiensuu, Eija Ferreira, Heli Helaakoski, Vesa Kyllönen, Juha Jokisaari, Esa Puukko

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

    6 Citations (Scopus)


    The purpose of this study was to develop an innovative supervisor system to assist the operators in an industrial manufacturing process to help discover new alternative solutions for improving both the products and the manufacturing process. This paper presents a solution for integrating different types of statistical modelling methods for a usable industrial application in quality monitoring. The two case studies demonstrating the usability of the tool were selected from a steel industry with different needs for knowledge presentation. The usability of the quality monitoring tool was tested in both case studies, both offline and online.

    Original languageEnglish
    Title of host publicationAdvances in Data Mining. Applications and Theoretical Aspects
    Subtitle of host publication18th Industrial Conference, ICDM 2018, Proceedings
    Number of pages12
    ISBN (Electronic)978-3-319-95786-9
    ISBN (Print)978-3-319-95785-2
    Publication statusPublished - 1 Jan 2018
    MoE publication typeNot Eligible
    Event18th Industrial Conference on Data Mining, ICDM 2018 - New York, United States
    Duration: 11 Jul 201812 Jul 2018

    Publication series

    SeriesLecture Notes in Computer Science
    Volume10933 LNAI


    Conference18th Industrial Conference on Data Mining, ICDM 2018
    Country/TerritoryUnited States
    CityNew York


    • Data mining
    • Knowledge representation
    • Machine learning
    • Online monitoring
    • Quality prediction
    • Smart manufacturing


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