From measurements to knowledge: Online quality monitoring and smart manufacturing

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

doi:10.1007/978-3-319-95786-9_2

From measurements to knowledge: Online quality monitoring and smart manufacturing

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

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	Advances in Data Mining. Applications and Theoretical Aspects
Subtitle of host publication	18th Industrial Conference, ICDM 2018, Proceedings
Publisher	Springer
Pages	17-28
Number of pages	12
ISBN (Electronic)	978-3-319-95786-9
ISBN (Print)	978-3-319-95785-2
DOIs	https://doi.org/10.1007/978-3-319-95786-9_2
Publication status	Published - 1 Jan 2018
MoE publication type	Not Eligible
Event	18th Industrial Conference on Data Mining, ICDM 2018 - New York, United States Duration: 11 Jul 2018 → 12 Jul 2018

Publication series

Series	Lecture Notes in Computer Science
Volume	10933 LNAI
ISSN	0302-9743

Conference

Conference	18th Industrial Conference on Data Mining, ICDM 2018
Country/Territory	United States
City	New York
Period	11/07/18 → 12/07/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

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

Access to Document

10.1007/978-3-319-95786-9_2

Cite this

Tamminen, S., Tiensuu, H., Ferreira, E., Helaakoski, H., Kyllönen, V., Jokisaari, J., & Puukko, E. (2018). From measurements to knowledge: Online quality monitoring and smart manufacturing. In Advances in Data Mining. Applications and Theoretical Aspects: 18th Industrial Conference, ICDM 2018, Proceedings (pp. 17-28). Springer. https://doi.org/10.1007/978-3-319-95786-9_2

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title = "From measurements to knowledge: Online quality monitoring and smart manufacturing",

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.",

keywords = "Data mining, Knowledge representation, Machine learning, Online monitoring, Quality prediction, Smart manufacturing",

author = "Satu Tamminen and Henna Tiensuu and Eija Ferreira and Heli Helaakoski and Vesa Kyll{\"o}nen and Juha Jokisaari and Esa Puukko",

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Tamminen, S, Tiensuu, H, Ferreira, E, Helaakoski, H , Kyllönen, V, Jokisaari, J & Puukko, E 2018, From measurements to knowledge: Online quality monitoring and smart manufacturing. in Advances in Data Mining. Applications and Theoretical Aspects: 18th Industrial Conference, ICDM 2018, Proceedings. Springer, Lecture Notes in Computer Science, vol. 10933 LNAI, pp. 17-28, 18th Industrial Conference on Data Mining, ICDM 2018, New York, United States, 11/07/18. https://doi.org/10.1007/978-3-319-95786-9_2

From measurements to knowledge: Online quality monitoring and smart manufacturing. / Tamminen, Satu; Tiensuu, Henna; Ferreira, Eija et al.
Advances in Data Mining. Applications and Theoretical Aspects: 18th Industrial Conference, ICDM 2018, Proceedings. Springer, 2018. p. 17-28 (Lecture Notes in Computer Science, Vol. 10933 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - From measurements to knowledge

T2 - 18th Industrial Conference on Data Mining, ICDM 2018

AU - Tamminen, Satu

AU - Tiensuu, Henna

AU - Ferreira, Eija

AU - Helaakoski, Heli

AU - Kyllönen, Vesa

AU - Jokisaari, Juha

AU - Puukko, Esa

PY - 2018/1/1

Y1 - 2018/1/1

N2 - 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.

AB - 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.

KW - Data mining

KW - Knowledge representation

KW - Machine learning

KW - Online monitoring

KW - Quality prediction

KW - Smart manufacturing

UR - https://www.scopus.com/pages/publications/85049892897

U2 - 10.1007/978-3-319-95786-9_2

DO - 10.1007/978-3-319-95786-9_2

M3 - Conference article in proceedings

AN - SCOPUS:85049892897

SN - 978-3-319-95785-2

T3 - Lecture Notes in Computer Science

SP - 17

EP - 28

BT - Advances in Data Mining. Applications and Theoretical Aspects

PB - Springer

Y2 - 11 July 2018 through 12 July 2018

ER -

Tamminen S, Tiensuu H, Ferreira E, Helaakoski H , Kyllönen V, Jokisaari J et al. From measurements to knowledge: Online quality monitoring and smart manufacturing. In Advances in Data Mining. Applications and Theoretical Aspects: 18th Industrial Conference, ICDM 2018, Proceedings. Springer. 2018. p. 17-28. (Lecture Notes in Computer Science, Vol. 10933 LNAI). doi: 10.1007/978-3-319-95786-9_2

From measurements to knowledge: Online quality monitoring and smart manufacturing

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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