System Reliability Analysis with In-House and Outsourced Components
Abstract
Outsourcing is a common practice for product development, but it also poses a challenge in system reliability prediction. Design details of outsourced components may not be available for system designers, making the system reliability prediction difficult. This paper discusses how to use a physics-based reliability approach to accurately predict system reliability for systems with both outsourced and in-house components. The accuracy is achieved by removing the assumption of independent component states. The idea is demonstrated with systems whose failures are caused by excessive loading. For system designers, physics-based limit-state functions are available for in-house components, and they also have reliability testing data provided by suppliers of outsourced components. Then system designers construct limit-state functions using the testing data for the outsourced components. With all the component limit-state functions available, the joint probability density function of the states of all the components in the system becomes available, resulting in accurate system reliability prediction. An engineering example is provided to demonstrate the proposed method.
Recommended Citation
Z. Hu and X. Du, "System Reliability Analysis with In-House and Outsourced Components," Proceedings of the 2nd International Conference on System Reliability and Safety (2017, Milan, Italy), vol. 2018-January, pp. 146 - 150, Institute of Electrical and Electronics Engineers (IEEE), Dec 2018.
The definitive version is available at https://doi.org/10.1109/ICSRS.2017.8272811
Meeting Name
2nd International Conference on System Reliability and Safety, ICSRS 2017 (2017: Dec. 20-22, Milan, Italy)
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Limit-State Function; Optimization; Statistical Dependence; System Reliability
International Standard Book Number (ISBN)
978-153863322-9
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Dec 2018
Comments
This material is based in part upon work supported by the National Science Foundation under Grant Number CMMI 1562593.