Options
Probabilistic maintenance optimization with respect to inspection quality
Date Issued
2018-09-12
Date Available
2018-11-27T09:39:40Z
Abstract
Maintenance scheduling and optimization against fatigue failures is of great interest for marine and offshore engineering in terms of safety assurance, integrity management and cost control. The main challenge is to make risk-informed and optimal maintenance decisions taking into account uncertainties associated with material properties, fatigue loads, modelling, inspection and maintenance methods. While optimization of inspection times has been the objectives of many studies, the influence and optimization of inspection qualities is not very clear. This paper has applied probabilistic fracture mechanics and reliability/risk methods to optimization of inspection quality as well as inspection time and revealed the effect of inspection quality on lifetime fatigue reliability. It is found that there is a reliability-based optimum inspection quality for maintenance scheduling, which is different from the cost-based optimum one. Better inspection quality than the optimum one can lead to excessive maintenance, which occurs when the effect of maintenance is not good, and the inspection quality applied is very good. Excessive maintenance can lead to increase of both expected failure costs and maintenance costs, and thus should be avoided.
Sponsorship
European Commission Horizon 2020
Type of Material
Conference Publication
Web versions
Language
English
Status of Item
Peer reviewed
Part of
Proceedings of the 16th International Probabilistic Workshop (IPW 2018)
Conference Details
The 16th International Probabilistic Workshop (IPW2018), Vienna, Austria, 12-14 September 2018
This item is made available under a Creative Commons License
File(s)
Name
Zou_etal_2018_Probabilistic maintenance optimization with respect to inspection quality.pdf
Size
291.17 KB
Format
Owning collection
Views
1131
Last Month
3
3
Acquisition Date
Apr 18, 2024
Apr 18, 2024
Downloads
159
Last Month
2
2
Acquisition Date
Apr 18, 2024
Apr 18, 2024