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Considering greenhouse gas emissions in maintenance optimisation

Wu, Shaomin, Wu, Di, Peng, Rui (2023) Considering greenhouse gas emissions in maintenance optimisation. European Journal of Operational Research, 307 (3). pp. 1135-1145. ISSN 0377-2217. (doi:10.1016/j.ejor.2022.10.007) (KAR id:97343)


Greenhouse gases (GHG) from human activities are the main contributor to climate change since the mid-20th century. Reducing the release of GHG emissions is becoming a thematic research topic in many research disciplines. In the reliability research community, there are research papers relating to reliability and maintenance for systems in power generation farms such as offshore farms. Nevertheless, there is sparse research that aims to optimise maintenance policies for reducing the GHG emissions from systems such as automotive vehicles or building service systems. To fill up this gap, this paper optimises replacement policies for systems that age and degrade and that produce GHG emissions (i.e., exhaust emissions) including the initial manufacturing GHG emissions produced during the manufacturing stage and the emissions generated during the operational stage. Both the exhaust emissions process and the failure process are considered as functions of two time scales (i.e., age and accumulated usage), respectively. Other factors that may affect the two processes such as ambient temperature and road conditions are depicted as random effects. Under these settings, the decision problem is a nonlinear programming problem subject to several constraints. Replacement policies are then developed. Numerical examples are provided to illustrate the proposed methods.

Item Type: Article
DOI/Identification number: 10.1016/j.ejor.2022.10.007
Uncontrolled keywords: Maintenance policy; greenhouse gas emissions; condition-based monitoring; two time scales; integer nonlinear programming
Subjects: H Social Sciences > HA Statistics
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Funders: University of Kent (
National Natural Science Foundation of China (
Depositing User: Shaomin Wu
Date Deposited: 08 Oct 2022 16:20 UTC
Last Modified: 04 Mar 2024 15:54 UTC
Resource URI: (The current URI for this page, for reference purposes)

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