Optimization of maintenance policy under parameter uncertainty using portfolio theory

Shaomin Wu, Frank P. A. Coolen, Bin Liu

Research output: Contribution to journal › Article

7 Citations (Scopus)

Abstract

In reliability mathematics, the optimization of a 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 article, are normally estimated based on either failure data collected from the field or lab data. The uncertainty associated with them is sensitive to several factors, including 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 the maintenance budget may not lead to optimal management of the model uncertainty and may lead to cost-ineffective decisions. To overcome this limitation, this article uses the concept of risk aggregation. It integrates the uncertainty of model parameters in the optimization of maintenance policies and then collectively optimizes 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.
LanguageEnglish
Pages711-721
Number of pages11
JournalIISE Transactions
Volume49
DOIs
Publication statusPublished - 16 Mar 2017

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Portfolio theory
Parameter uncertainty
Uncertainty
Information costs
Renewal
Decision costs
Derivatives
Optimal management
Factors
Mathematics
Risk aggregation
Model uncertainty

Keywords

  • Maintenance
  • parameter uncertainty
  • portfolio theory
  • maintenance policy

Cite this

Wu, Shaomin ; Coolen, Frank P. A. ; Liu, Bin. / Optimization of maintenance policy under parameter uncertainty using portfolio theory. In: IISE Transactions. 2017 ; Vol. 49. pp. 711-721.
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Wu, S, Coolen, FPA & Liu, B 2017, 'Optimization of maintenance policy under parameter uncertainty using portfolio theory' IISE Transactions, vol. 49, pp. 711-721. https://doi.org/10.1080/24725854.2016.1267881

Optimization of maintenance policy under parameter uncertainty using portfolio theory. / Wu, Shaomin; Coolen, Frank P. A. ; Liu, Bin.

In: IISE Transactions, Vol. 49, 16.03.2017, p. 711-721.

Research output: Contribution to journal › Article

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AU - Wu, Shaomin

AU - Coolen, Frank P. A.

AU - Liu, Bin

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N2 - In reliability mathematics, the optimization of a 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 article, are normally estimated based on either failure data collected from the field or lab data. The uncertainty associated with them is sensitive to several factors, including 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 the maintenance budget may not lead to optimal management of the model uncertainty and may lead to cost-ineffective decisions. To overcome this limitation, this article uses the concept of risk aggregation. It integrates the uncertainty of model parameters in the optimization of maintenance policies and then collectively optimizes 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.

AB - In reliability mathematics, the optimization of a 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 article, are normally estimated based on either failure data collected from the field or lab data. The uncertainty associated with them is sensitive to several factors, including 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 the maintenance budget may not lead to optimal management of the model uncertainty and may lead to cost-ineffective decisions. To overcome this limitation, this article uses the concept of risk aggregation. It integrates the uncertainty of model parameters in the optimization of maintenance policies and then collectively optimizes 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.

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Wu S, Coolen FPA, Liu B. Optimization of maintenance policy under parameter uncertainty using portfolio theory. IISE Transactions. 2017 Mar 16;49:711-721. https://doi.org/10.1080/24725854.2016.1267881

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