A reliability analysis method based on the mixed correlated competition model considering multi-performance degradation and sudden failures. (April 2023)

• Record Type: Journal Article
• Authors: Pan, Guangze; Guo, Guangkuo; Li, Dan; Li, Yaqiu; Li, Qian; Liu, Wenwei
• Is Part Of: Engineering failure analysis. Volume 146(2023)
• Publication Date: 2023-04
• Subjects: Multi-performance degradation -- Sudden failures -- Mixed correlated competition -- Nonlinear Wiener process model -- Reliability analysis; System failures (Engineering) -- Periodicals; Fracture mechanics -- Periodicals; Reliability (Engineering) -- Periodicals; Pannes -- Périodiques; Rupture, Mécanique de la -- Périodiques; Fiabilité -- Périodiques; Fracture mechanics; Reliability (Engineering); System failures (Engineering); Periodicals; Electronic journals; 620.112
• DOI: 10.1016/j.engfailanal.2023.107126
• Languages: English
• ISSNs: 1350-6307

Abstract

Highlights: Describing the degradation failure by the nonlinear Wiener process model based on the time scale transformation function. Proposing a reliability evaluation method based on the two-phase maximum likelihood function. Establishing a systematic mixed correlated competition model. Taking into account the interaction between multi-performance degradation and sudden failures. Abstract: Complex products usually fail due to competing multi-performance degradation and sudden failure modes. The correlations between competing failure modes, including among multi-performance degradation failures and between degradation and sudden failures, must be considered in reliability analysis. This paper proposes a general reliability analysis method that considers such cases of complex mixed correlated competition. Firstly, a nonlinear Wiener process model based on a time-scale transformation function is applied to model performance degradation failure, and a multi-performance-degradation correlated-competition model based on a Copula function is constructed, which considers the correlated competition between multi-performance degradation failures. Secondly, a three-parameter Weibull distribution is used to model sudden failures, and an evaluation method based on nonlinear planning-maximum likelihood estimation is proposed to estimate its parameters. Thirdly, a mixed correlated-competition model of multi-performance degradation and sudden failures is proposed for product reliability evaluation. Finally, a servo system experiment is used for demonstration. The experimental results demonstrate that the proposed method achieves higher evaluation accuracy and has wider applicability than existing methods, which ignore mixed correlated competition.