| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Condition-based maintenance decision making : a practical approach for marine vessels |
| Autor/-in: | Goren Huber, Lilach Kunz, Simon Dettling, Marcel |
| Seite(n): | 357 |
| Seiten bis: | 365 |
| Angaben zur Konferenz: | 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017 |
| Erscheinungsdatum: | 2017 |
| Verlag / Hrsg. Institution: | Jost Institute for Tribotechnology |
| Verlag / Hrsg. Institution: | Lancashire |
| ISBN: | 9781909755109 |
| Sprache: | Englisch |
| Schlagwörter: | Condition based maintenance; Decision making; Degradation modeling; Uncertainty analysis; Optimization |
| Fachgebiet (DDC): | 620: Ingenieurwesen |
| Zusammenfassung: | Condition monitoring and predictive maintenance are gaining importance amongst researchers and practitioners. Many technical systems, however, do not get to profit from the growing amount of knowledge in these fields. The reason lies in the lack of high quality monitoring data, largely due to the reluctance of system owners to invest in monitoring equipment and data processing. This leads to a vicious circle that limits the applicability of condition based maintenance. The need for simple yet effective schemes for data-driven maintenance optimization motivated the present research. This paper demonstrates the development of such a scheme for maintenance optimization of marine vessels based on the readily available data, thereby lowering the entry barrier for ship operators and promoting future improvements of the data quality. The approach combines data-driven with physical modeling, and uses the models as an input for a constrained optimization algorithm based on linear programming and a Monte-Carlo-based uncertainty analysis. The algorithm allows for a gradual enhancement of the data-driven component upon acquisition of more and better data. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/8014 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | Lizenz gemäss Verlagsvertrag |
| Departement: | School of Engineering |
| Organisationseinheit: | Institut für Datenanalyse und Prozessdesign (IDP) |
| Publiziert im Rahmen des ZHAW-Projekts: | Energy Optimization for Vessel Operations |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
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Goren Huber, L., Kunz, S., & Dettling, M. (2017). Condition-based maintenance decision making : a practical approach for marine vessels [Conference paper]. 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017, 357–365.
Goren Huber, L., Kunz, S. and Dettling, M. (2017) ‘Condition-based maintenance decision making : a practical approach for marine vessels’, in 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017. Lancashire: Jost Institute for Tribotechnology, pp. 357–365.
L. Goren Huber, S. Kunz, and M. Dettling, “Condition-based maintenance decision making : a practical approach for marine vessels,” in 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017, 2017, pp. 357–365.
GOREN HUBER, Lilach, Simon KUNZ und Marcel DETTLING, 2017. Condition-based maintenance decision making : a practical approach for marine vessels. In: 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017. Conference paper. Lancashire: Jost Institute for Tribotechnology. 2017. S. 357–365. ISBN 9781909755109
Goren Huber, Lilach, Simon Kunz, and Marcel Dettling. 2017. “Condition-Based Maintenance Decision Making : A Practical Approach for Marine Vessels.” Conference paper. In 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017, 357–65. Lancashire: Jost Institute for Tribotechnology.
Goren Huber, Lilach, et al. “Condition-Based Maintenance Decision Making : A Practical Approach for Marine Vessels.” 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017, Jost Institute for Tribotechnology, 2017, pp. 357–65.
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