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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Pattern Recognition for Predictive Analysis in Automotive Industry
verfasst von : Veronika Simoncicova, Lukas Hrcka, Lukas Spendla, Pavol Tanuska, Pavel Vazan
Erschienen in: Cybernetics and Mathematics Applications in Intelligent Systems
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Abstract
Predictive maintenance (PdM) techniques are designed to help identify the condition of devices in order to predict when maintenance should be performed. The ultimate goal of PdM is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective and before the equipment loses performance within a threshold. Currently, reducing service costs and losses due to downtime is one of the ways to increase your profits and success in the market. We tried to identify problem messages and failures from the manufacturing data example set from car body work. Two different data sets were joined and we designed a process to identify message and failure alerts preceding errors.