Skip to main content

Research Repository

Advanced Search

Optimisation of maintenance policy under parameter uncertainty using portfolio theory

Wu, S.; Coolen, F.P.A.; Liu, B.

Optimisation of maintenance policy under parameter uncertainty using portfolio theory Thumbnail


Authors

S. Wu

B. Liu



Abstract

In reliability mathematics, optimisation of maintenance policy is derived based on reliability indexes such as the reliability or its derivatives (e.g., the cumulative failure intensity or the renewal function) and the associated cost information. The reliability indexes, also referred to as models in this paper, are normally estimated based on either failure data collected from the field or lab data. The uncertainty associated with them is sensitive to factors such as the sparsity of data. For a company that maintains a number of different systems, developing maintenance policies for each individual system separately and then allocating maintenance budget may not lead to optimal management of the model uncertainty and may lead to cost-ineffective decisions. To overcome this limitation, this paper uses the concept of risk aggregation. It integrates the uncertainty of model parameters in optimisation of maintenance policies and then collectively optimises maintenance policies for a set of different systems, using methods from portfolio theory. Numerical examples are given to illustrate the application of the proposed methods.

Citation

Wu, S., Coolen, F., & Liu, B. (2017). Optimisation of maintenance policy under parameter uncertainty using portfolio theory. IISE Transactions, 49(7), 711-721. https://doi.org/10.1080/24725854.2016.1267881

Journal Article Type Article
Acceptance Date Nov 25, 2016
Online Publication Date Dec 6, 2016
Publication Date Jul 3, 2017
Deposit Date Nov 26, 2016
Publicly Available Date Dec 6, 2017
Journal IISE Transactions.
Print ISSN 2472-5854
Electronic ISSN 2472-5862
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 49
Issue 7
Pages 711-721
DOI https://doi.org/10.1080/24725854.2016.1267881
Public URL https://durham-repository.worktribe.com/output/1369688

Files






You might also like



Downloadable Citations