Interactive Visual Analytics of Production Data: Predictive Manufacturing

Juhani Heilala, Paula Järvinen, Pekka Siltanen, Montonen Jari, Markku Hentula, Mikael Haag

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


    Manufacturing creates a lot of data, and this is increasing due to digitalization of manufacturing, industrial Internet of Things (IIoT) and needs for product traceability as well as predictive maintenance. Typically data from production material flow is not analyzed and thus the improvement potential is not found. There is need for interactive analytics tools that can turn raw data from heterogeneous data sources e.g. starting from sensor data, manufacturing IT systems, (e.g. Enterprise Resource Planning, ERP, Manufacturing Execution System, MES and Supervisory Control And Data Acquisition, SCADA), into meaningful information and predictions-and presented on easy-to-use interfaces. This paper presents a feasibility study focusing on interactive visual analytics of manufacturing data set carried out at VTT Technical Research Centre of Finland Ltd.
    Original languageEnglish
    Title of host publication Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
    PublisherLinköping University Electronic Press
    Number of pages6
    ISBN (Print)978-91-7685-399-3
    Publication statusPublished - 2018
    MoE publication typeA4 Article in a conference publication
    Event9th Eurosim Congress on Modelling and Simulation: 57th SIMS conference on Simulation and Modelling (SIMS 2016) - Oulu, Finland
    Duration: 12 Sept 201616 Sept 2016

    Publication series

    SeriesLinköping Electronic Conference Proceedings


    Conference9th Eurosim Congress on Modelling and Simulation
    Abbreviated titleEUROSIM 2016
    OtherThe EUROSIM 2016 Congress provides a forum where modelling and simulation professionals from industry, society and science exchange knowledge, experiences and strengthen multidisciplinary network.


    • manufacturing industry
    • statistical analysis
    • machine learning
    • visual analytics
    • industrial internet of things


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