A Model-based RCM Analysis Method

Mian, Zhibao; Jia, Shuli; Shi, Xiaodong; Tang, Cairong; Chen, Junjie; Gao, Yaqing

Abstract

The reliability-centered maintenance (RCM) is one of the most advanced maintenance plan generating technologies for equipments. At present, the key technologies such as FMEA and FMECA supporting the RCM analysis remains in the manual stage in some enterprises. The disadvantages are time-consuming, labour-intensive and error-prone. For complex systems containing thousands of components, to achieve a fast and effective FMECA analysis is difficult. RCM should benefit from the most advanced model-based systems engineering methods. In this paper, a model-based RCM analysis framework (MRAF) is presented. Based on this framework, RCM analysts can use model-based reliability analysis techniques, such as AADL, to model the system architecture and faults information. Then the AADL-based analysis platform OSATE can be used to automatically produce the FMEA. By combining the generated FMEA with the criticality analysis (CA) technology, this paper can semiautomatically generate the FMECA for equipments and systems being analyzed by RCM.

Citation

Mian, Z., Jia, S., Shi, X., Tang, C., Chen, J., & Gao, Y. (2020). A Model-based RCM Analysis Method. In IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C) (301-307). https://doi.org/10.1109/QRS-C51114.2020.00059

• Conference Name: 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C)
• Conference Location: Macau, China
• Start Date: Dec 11, 2020
• End Date: Dec 14, 2020
• Acceptance Date: Sep 20, 2020
• Publication Date: Dec 21, 2020
• Deposit Date: Jul 12, 2022
• Publisher: Institute of Electrical and Electronics Engineers
• Pages: 301-307
• Book Title: IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C)
• ISBN: 9781728189154
• DOI: https://doi.org/10.1109/QRS-C51114.2020.00059
• Keywords: Reliability-centered maintenance , AADL , MRAF , FMEA , FMECA
• Public URL: https://hull-repository.worktribe.com/output/4028773
• Publisher URL: https://ieeexplore.ieee.org/document/9282666/