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

Németh Martin () and Michaľčonok German ()
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Németh Martin: 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
Michaľčonok German: 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, 2016, vol. 24, issue 39, 111-116

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.

Keywords: Predictive maintenance; data mining; clustering; distance matrix; production process (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:repfms:v:24:y:2016:i:39:p:111-116:n:14

DOI: 10.1515/rput-2016-0024

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