Interactive Visual Analytics of Production Data: Predictive Manufacturing

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

    Abstract

    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 publication9th EUROSIM Congress on Modelling and Simulation
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages166-171
    ISBN (Print)978-1-5090-4119-0
    Publication statusAccepted/In press - 2016
    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 Sep 201616 Sep 2016

    Conference

    Conference9th Eurosim Congress on Modelling and Simulation
    Abbreviated titleEUROSIM 2016
    CountryFinland
    CityOulu
    Period12/09/1616/09/16
    OtherThe EUROSIM 2016 Congress provides a forum where modelling and simulation professionals from industry, society and science exchange knowledge, experiences and strengthen multidisciplinary network.

    Fingerprint

    Enterprise resource planning
    Data acquisition
    Sensors
    Internet of things

    Keywords

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

    Cite this

    Heilala, J., Järvinen, P., Siltanen, P., Jari, M., Hentula, M., & Haag, M. (Accepted/In press). Interactive Visual Analytics of Production Data: Predictive Manufacturing. In 9th EUROSIM Congress on Modelling and Simulation (pp. 166-171). IEEE Institute of Electrical and Electronic Engineers .
    Heilala, Juhani ; Järvinen, Paula ; Siltanen, Pekka ; Jari, Montonen ; Hentula, Markku ; Haag, Mikael. / Interactive Visual Analytics of Production Data : Predictive Manufacturing. 9th EUROSIM Congress on Modelling and Simulation. IEEE Institute of Electrical and Electronic Engineers , 2016. pp. 166-171
    @inproceedings{af7ea5e781674c16a16cdf32a3abefd7,
    title = "Interactive Visual Analytics of Production Data: Predictive Manufacturing",
    abstract = "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.",
    keywords = "manufacturing industry, statistical analysis, machine learning, visual analytics, industrial internet of things",
    author = "Juhani Heilala and Paula J{\"a}rvinen and Pekka Siltanen and Montonen Jari and Markku Hentula and Mikael Haag",
    note = "Proceedings final version is not yet published. SDA: SHP: ForIndustry Project : 109807",
    year = "2016",
    language = "English",
    isbn = "978-1-5090-4119-0",
    pages = "166--171",
    booktitle = "9th EUROSIM Congress on Modelling and Simulation",
    publisher = "IEEE Institute of Electrical and Electronic Engineers",
    address = "United States",

    }

    Heilala, J, Järvinen, P, Siltanen, P, Jari, M, Hentula, M & Haag, M 2016, Interactive Visual Analytics of Production Data: Predictive Manufacturing. in 9th EUROSIM Congress on Modelling and Simulation. IEEE Institute of Electrical and Electronic Engineers , pp. 166-171, 9th Eurosim Congress on Modelling and Simulation, Oulu, Finland, 12/09/16.

    Interactive Visual Analytics of Production Data : Predictive Manufacturing. / Heilala, Juhani; Järvinen, Paula; Siltanen, Pekka; Jari, Montonen; Hentula, Markku; Haag, Mikael.

    9th EUROSIM Congress on Modelling and Simulation. IEEE Institute of Electrical and Electronic Engineers , 2016. p. 166-171.

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

    TY - GEN

    T1 - Interactive Visual Analytics of Production Data

    T2 - Predictive Manufacturing

    AU - Heilala, Juhani

    AU - Järvinen, Paula

    AU - Siltanen, Pekka

    AU - Jari, Montonen

    AU - Hentula, Markku

    AU - Haag, Mikael

    N1 - Proceedings final version is not yet published. SDA: SHP: ForIndustry Project : 109807

    PY - 2016

    Y1 - 2016

    N2 - 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.

    AB - 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.

    KW - manufacturing industry

    KW - statistical analysis

    KW - machine learning

    KW - visual analytics

    KW - industrial internet of things

    M3 - Conference article in proceedings

    SN - 978-1-5090-4119-0

    SP - 166

    EP - 171

    BT - 9th EUROSIM Congress on Modelling and Simulation

    PB - IEEE Institute of Electrical and Electronic Engineers

    ER -

    Heilala J, Järvinen P, Siltanen P, Jari M, Hentula M, Haag M. Interactive Visual Analytics of Production Data: Predictive Manufacturing. In 9th EUROSIM Congress on Modelling and Simulation. IEEE Institute of Electrical and Electronic Engineers . 2016. p. 166-171