Reliability Modeling and Evaluation for Complex Systems Subject to New Dependent Competing Failure Process

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 17
• Main Authors: Hao, Huibing, Li, Chunping
• Format: Journal Article
• Language: English
• Published: New York Hindawi 10.08.2022; John Wiley & Sons, Inc
• Subjects: Competition; Complex systems; Component reliability; Crack propagation; Degradation; Engineering; Failure; Fatigue failure; Fracture mechanics; Gaussian process; Normal distribution; Reliability analysis
• DOI: 10.1155/2022/5432809
• ISSN: 1024-123X

The objective of this study is to construct some system-level reliability models subject to new dependent competing failure process of the soft failure process and hard failure process. In those complex system-level models, the soft failure caused by continuous degradation and sudden degradation increases by random shocks and hard failure due to the same shock process; in addition, the bidirectional effects between natural degradation and random shock are considered in this study; in other words, the random shock can bring additional degradation, and the natural degradation may also impact the shock process. Therefore, the soft failure process and hard failure process are dependent. By using the cumulative shock model and Gaussian stochastic degradation process with line mean value and line standard deviation, five types of reliability models were established: (1) single component model; (2) series system model; (3) parallel system model; (4) series-parallel system model; and (5) parallel-series system model. Finally, an example of fatigue crack growth dataset is taken to verify the effectiveness of the established model and method, and some sensitivity analyses are given. The results show that the bidirectional effects can significantly accelerate the system failure, and the impact of natural degradation process to random shocks should not be ignored. In addition, the results also show that random shock and failure threshold have significant effects on the different complex systems.