Bayesian information fusion for degradation analysis of deteriorating products with individual heterogeneity. (August 2019)

• Record Type: Journal Article
• Authors: Guo, Junyu; Huang, Hong-Zhong; Peng, Weiwen; Zhou, Jie
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 233:Number 4(2019:Aug.)
• Page Start: 615
• Page End: 622
• Publication Date: 2019-08
• Subjects: Reliability analysis -- performance degradation -- Gamma process -- individual heterogeneity -- information fusion; Reliability (Engineering) -- Mathematical models -- Periodiclals; Risk assessment -- Mathematical models -- Periodicals; Engineering design -- Mathematical models -- Periodicals; 620.00452
• DOI: 10.1177/1748006X18808964
• Languages: English
• ISSNs: 1748-006X

Abstract

Degradation analysis is a popular and effective method for reliability analysis of long-life and high-reliability products. However, for newly developed products, especially for highly customized products with small sample size, the challenge of sparse degradation observations with product heterogeneity is still an open issue deserving further research. In this article, Bayesian degradation analysis is presented for reliability analysis of products with heterogeneity. The degradation process is modeled by a Gamma process. Random effects are incorporated in the Gamma process model for characterizing the individual heterogeneity. To improve the precision of parameter estimation and degradation analysis, a Bayesian information fusion is presented to leverage degradation information from multiple sources. The proposed model is demonstrated through degradation-based reliability analysis of heavy-duty machine tool's spindle system, which is characterized as degradation analysis with individual heterogeneity and information fusion.