From measurements to knowledge : online quality monitoring and smart manufacturing

Tamminen, Satu; Tiensuu, Henna; Ferreira, Eija; Helaakoski, Heli; Kyllönen, Vesa; Jokisaari, Juha; Puukko, Esa (2018-07-04)
 
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https://doi.org/10.1007/978-3-319-95786-9_2

Tamminen, Satu
Tiensuu, Henna
Ferreira, Eija
Helaakoski, Heli
Kyllönen, Vesa
Jokisaari, Juha
Puukko, Esa
Springer Nature
04.07.2018

Tamminen S. et al. (2018) From Measurements to Knowledge - Online Quality Monitoring and Smart Manufacturing. In: Perner P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2018. Lecture Notes in Computer Science, vol 10933. Springer, Cham

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© Springer International Publishing AG, part of Springer Nature 2018. This is a post-peer-review, pre-copyedit version of an article published in Advances in Data Mining. Applications and Theoretical Aspects 18th Industrial Conference, ICDM 2018, New York, NY, USA, July 11-12, 2018, Proceedings. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-95786-9_2
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doi:https://doi.org/10.1007/978-3-319-95786-9_2
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Abstract

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.

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