@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 = "Project : 109807 ; 9th Eurosim Congress on Modelling and Simulation : 57th SIMS conference on Simulation and Modelling (SIMS 2016), EUROSIM 2016 ; Conference date: 12-09-2016 Through 16-09-2016",
year = "2018",
doi = "10.3384/ecp17142181",
language = "English",
isbn = "978-91-7685-399-3",
series = "Link{\"o}ping Electronic Conference Proceedings",
publisher = "Link{\"o}ping University Electronic Press",
pages = "181--186",
booktitle = "Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016",
address = "Sweden",
}