<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This article is devoted to the initial phase of data analysis of failure data from process control systems. Failure data can be used for example to detect weak spots in a production process, but also for failure prediction. To achieve these goals data mining techniques can be used. In this article, we propose a method to prepare and transform failure data from process control systems for application of data mining algorithms, especially cluster analysis.</p></abstract>

This article is devoted to the initial phase of data analysis of failure data from process control systems. Failure data can be used for example to detect weak spots in a production process, but also for failure prediction. To achieve these goals data mining techniques can be used. In this article, we propose a method to prepare and transform failure data from process control systems for application of data mining algorithms, especially cluster analysis.

Preparation and Cluster Analysis of Data from the Industrial Production Process for Failure Prediction

Institute of Applied Informatics, Automation and Mechatronics, Faculty of Materials Science and Technology in Trnava, Slovak University of Technology in Bratislava, Ulica Jána Bottu 2781/25, 917 24 Trnava, Slovak Republic

Research Papers Faculty of Materials Science and Technology Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This article is devoted to the initial phase of data analysis of failure data from process control systems. Failure data can be used for example to detect weak...

Preparation and Cluster Analysis of Data from the Industrial Production Process for Failure Prediction

Online veröffentlicht: 04. Apr. 2017

Seitenbereich: 111 - 116

DOI: https://doi.org/10.1515/rput-2016-0024

Schlüsselwörter
Predictive maintenance, data mining, clustering, distance matrix, production process

© 2016 Martin Németh et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Preparation and Cluster Analysis of Data from the Industrial Production Process for Failure Prediction

Online veröffentlicht: 04. Apr. 2017

Seitenbereich: 111 - 116

DOI: https://doi.org/10.1515/rput-2016-0024

SchlüsselwörterPredictive maintenance, data mining, clustering, distance matrix, production process

© 2016 Martin Németh et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Predictive maintenance, data mining, clustering, distance matrix, production process