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Kovacs, K., Ansari, F., & Sihn, W. (2021). A modified Weibull model for service life prediction and spare parts forecast in heat treatment industry. In Procedia Manufacturing (pp. 172–177). https://doi.org/10.1016/j.promfg.2021.07.026
E330-02-1 - Forschungsgruppe Smart and Knowledge Based Maintenance E330-02 - Forschungsbereich Betriebstechnik, Systemplanung und Facility Management
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Erschienen in:
Procedia Manufacturing
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Datum (veröffentlicht):
2021
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Veranstaltungsname:
10th International Conference on Digital Enterprise Technology 2021
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Veranstaltungszeitraum:
11-Okt-2021 - 13-Okt-2021
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Veranstaltungsort:
Budapest, Ungarn
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Umfang:
6
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Keywords:
Artificial Intelligence; Digitalization; Industrial and Manufacturing Engineering; Smart maintenance; Service life prediction; Weibull distribution; Spare parts forcast
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Abstract:
The ongoing digitization of the industry leads to new opportunities in industrial maintenance. Several concepts for smart maintenance have been published in literature, however, their application remains limited in industrial practice. To close the existing gap between research and practice, a novel practice-oriented approach is presented. A modified Weibull model is developed and embodied into a ...
The ongoing digitization of the industry leads to new opportunities in industrial maintenance. Several concepts for smart maintenance have been published in literature, however, their application remains limited in industrial practice. To close the existing gap between research and practice, a novel practice-oriented approach is presented. A modified Weibull model is developed and embodied into a digital assistance system to visualize and predict remaining service life and to forecast the required number of spare parts. The developed model has been implemented in the use case in the heat treatment industry, and the results are presented to demonstrate the effectiveness of the proposed approach.
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Forschungsschwerpunkte:
Digital Transformation in Manufacturing: 50% Automation and Robotics: 50%
