Publication type: Conference paper
Type of review: Peer review (publication)
Title: Condition-based maintenance decision making : a practical approach for marine vessels
Authors: Goren Huber, Lilach
Kunz, Simon
Dettling, Marcel
Page(s): 357
Pages to: 365
Conference details: 30th Conference for Condition Monitoring and Diagnostic Engineering Management, Lancashire, United Kingdom, July 2017
Issue Date: 2017
Publisher / Ed. Institution: Jost Institute for Tribotechnology
Publisher / Ed. Institution: Lancashire
ISBN: 9781909755109
Language: English
Subjects: Condition based maintenance; Decision making; Degradation modeling; Uncertainty analysis; Optimization
Subject (DDC): 620: Engineering
Abstract: 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
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Data Analysis and Process Design (IDP)
Published as part of the ZHAW project: Energy Optimization for Vessel Operations
Appears in collections: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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