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As the core foundation of reliability engineering and one of the most crucial aspects of general quality, reliability has been attracting increasing attention from industry and academia. Numerous publications on reliability analysis (RA) have appeared in academic journals, conference proceedings, and technical reports. However, there has not been a systematic summary that covers RA data, models, methods, indicators, and software comprehensively. To fill this gap, this paper analyzed the challenges and the state of the art, as well as determined the future prospects for research on RA. This paper introduces the features of modern complex electromechanical systems (CES), then summarizes the current challenges to the RA of CES. Next, it reviews the latest developments, such as reliability theories, models, methods, and software, then summarizes and compares their advantages and limitations. Finally, it discusses future prospects from the perspectives of reliability data, modeling, decoupling, evaluation indicators, and timely prediction. It is expected that this paper would serve as an introduction to RA for researchers new to this field and as a summary of the current frontiers of RA for experienced researchers. [ABSTRACT FROM AUTHOR]

Many conventional reliability analysis methods for multi-state systems assume independence among the various subsystems. To avoid this, we propose a probabilistic model checking-based approach for failure correlation analysis of multi-state systems. First, an improved Apriori algorithm is used to determine the effect of a subsystem failure on the associated subsystems. Next, a copula function is applied to establish the relationship between failures of the associated subsystems. Finally, probabilistic model-checking is used to analyze the reliability of the entire system and all its subsystems. The effectiveness of the proposed method is verified using an application involving offshore wind turbines. The results show that the proposed method can be used flexibly and effectively for multi-state system reliability analysis. Moreover, the proposed method lays the foundation for system maintenance strategy formulation and other engineering applications. [ABSTRACT FROM AUTHOR]

High reliability and security have become the hallmarks of complex electromechanical systems. Owing to the difficulties in fault data collection, ambiguity and uncertainty have been inevitably associated with complex electromechanical systems. Thus, the ability to perform reliability evaluation using scarce fault data is of immense significance to these machines and is the focus of this study. A similarity based cloud model is proposed to evaluate the running state of complex electromechanical systems. By combining objective and subjective factors, the reliability of complex electromechanical systems is evaluated by calculating the similarity between the cloud models of actual and standardised states. Next, the inverter of an offshore wind turbine is used to verify the accuracy and effectiveness of the proposed approach. The cloud model based framework for reliability evaluation inherits the preponderance of the uncertainty problem, overcomes the drawbacks of the current reliability approaches, and provides a theoretical basis, as well as a practical approach for the maintenance and repair of complex electromechanical systems with missing fault data. Additionally, it also provides a new methodology for solving the uncertainty problems caused by paucity of data. [ABSTRACT FROM AUTHOR]

Due to the propagation, amplification, and concatenation in a failure process, the reliabilities of repairable multistate complex mechanical systems (RMCMSs) may be affected by a significant fluctuation due to a small exception associated with a reliability indicator. Focused on the problems arising from the lack of propagation relationships among fault modes, functional components, and failure causes in conventional reliability models, a novel framework for reliability modelling is proposed to comprehensively analyse the reliabilities of RMCMSs. First, the reliability models are abstracted as weighted and directed networks with five layers. Second, an improved failure mode and effects analysis (IFMEA) method combined with the D‐number method and VIKOR approach is presented to determine the importance of reliability nodes. Third, a cut set of the reliability model is generated by any exception of a reliability indicator by considering the propagation relationships, and the reliability sensibility index is defined to characterize the fluctuations in system reliability. The effectiveness of the proposed framework is demonstrated in an actual reliability modelling application. As an intuitive method, the proposed framework inherits the advantages of conventional models but overcomes the drawbacks of these existing methods. Therefore, this method can be flexibly and efficiently used in the reliability modelling of RMCMSs. Moreover, the approach provides a foundation for comprehensive and dynamic reliability analysis and the failure mechanism mining of RMCMSs, and it can be used in other engineering applications. [ABSTRACT FROM AUTHOR]

In view of the problems of degradation index construction and predicted lag of similarity-based methods, a degradation degree considered method for remaining useful life prediction based on similarity is proposed. The effectiveness of the proposed method is demonstrated by using turbofan engine data from NASA and a real case study. [ABSTRACT FROM AUTHOR]

• A novel F2G model is proposed for the reliability modeling of coupled faults. • The functional logics and fault logics are integrated in F2G model. • All the standardized meta models and calculation rules used in F2G are defined. • The proposed method is validated by empirical case. Reliability analysis plays a crucial role in revealing the failure causes and determining the improvement measures for reliability growth. However, reliability analysis of complex equipment with coupled faults still corresponds to a challenging task, due to unclear coupling mechanism and unsuitable analysis model. A down-top, deductive modeling method, named as fault-function graph (F2G), is proposed. First, the meta models are defined to normalize all the atomic faults, coupling relations and coupling forms in modeling. Next, an initial fault model is constructed based on typical fault-relations and coupling forms. Furthermore, the functional hierarchy of fault determined by IDEF0 is appended. Lastly, the rigorous modeling rules and computing processes are explained based on an actual case. As a graphical modeling method, it handles the coupling faults by integrating the system functional and fault information. Exploiting the advantages of conventional models, the coupling relations are quantified, and the false relations are detected based on functional constraints. Therefore, the proposed method can be used flexibly in the reliability modeling of coupled faults. Moreover, it provides a foundation for the comprehensive and dynamic reliability analysis and the failure mechanism mining of complex equipment, and it can be used in other engineering applications as well. [ABSTRACT FROM AUTHOR]