Multi-state Aperiodic Inspection-based Maintenance Strategy Optimization using Real-time Data
Authors: 
Jitong Zeng, Pan HeAuthors Info & Claims
Pages 670 - 677
Abstract
For complex engineering systems, proper equipment maintenance is one of the most important means to ensure the system’s safety, reliability, and availability. To further reduce the maintenance cost of the system, this paper proposes a method to optimize the inspection and maintenance strategy based on real-time condition monitoring data. The method relies on a data-driven predictive model to construct a system Remaining Useful Life (RUL) distribution, converted into a system reliability index related to the system operating state. A clustering algorithm classifies the classes of degradation states during system operation. Different degradation state classes correspond to different inspection decision variables, which flexibly determine the optimal inspection interval and maintenance decision according to the system operation status. The performance of the proposed dynamic predictive maintenance strategy measures the maintenance cost rate (MCR) using the NASA aircraft engine dataset. The experimental results show that the method effectively reduces the inspection and maintenance cost of the system.
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- Multi-state Aperiodic Inspection-based Maintenance Strategy Optimization using Real-time Data
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Published In
March 2023
824 pages
ISBN:9781450399029
DOI:10.1145/3594315
Copyright © 2023 ACM.
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Association for Computing Machinery
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Publication History
Published: 02 August 2023
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ICCAI 2023
ICCAI 2023: 2023 9th International Conference on Computing and Artificial Intelligence
March 17 - 20, 2023
Tianjin, China
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