Log-based predictive maintenance in discrete parts manufacturing

Titel in Übersetzung: Log-based predictive maintenance in discrete parts manufacturing

Clemens Gutschi, Nikolaus Furian, Dietmar Neubacher

Publikation: KonferenzbeitragAbstractBegutachtung


The performance of discrete parts manufacturing systems is heavily influenced by unplanned machine breakdowns. Predictive maintenance allows for the conversation of unplanned machine breakdowns to scheduled corrective maintenance actions. We present a data-driven log-based approach for estimating the probability of machine breakdowns during specified time intervals in the future. Machine learning algorithms are utilized for a specific use-case which is based on real-world data-sets including machine log messages, event logs and operational information. We will present an overview on predictive maintenance strategies as well as applied data-preparation, feature-engineering and machine learning methods for estimating the remaining useful lifetime. The comparison of two different methods for RUL-estimation is indicating that machine failures can be predicted up to 168 hours in advance with promising precision and hit-rate.
Titel in ÜbersetzungLog-based predictive maintenance in discrete parts manufacturing
PublikationsstatusVeröffentlicht - Juni 2019
Veranstaltung30th European Conference on Operational Research: 30th European Conference on Operational Research ​ - University College Dublin, Dublin, Irland
Dauer: 23 Juni 201926 Juni 2019


Konferenz30th European Conference on Operational Research
KurztitelEURO 2019

ASJC Scopus subject areas

  • Artificial intelligence
  • Wirtschaftsingenieurwesen und Fertigungstechnik
  • Managementlehre und Operations Resarch
  • Steuerungs- und Systemtechnik

Fields of Expertise

  • Mobility & Production


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