A new approach for risk assessment of failure modes considering risk interaction and propagation effects

• Published in: Reliability engineering & system safety Vol. 216; p. 108044
• Main Authors: Wang, Qun, Jia, Guozhu, Jia, Yuning, Song, Wenyan
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.12.2021; Elsevier BV
• Subjects: Attenuation; Attenuation effect; Failure analysis; Failure mode and effect analysis (FMEA); Failure modes; Negative influence; Positive influence; Propagation; Propagation modes; Reliability engineering; Risk assessment; Risk management; Risk propagation; Search algorithms; System reliability; Attenuation effect; Positive influence; Risk propagation; Failure mode and effect analysis (FMEA); Negative influence
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2021.108044

•The method considers the initial strength effect of failure mode on the risk propagation.•The method can deal with positive and negative interactions between failure modes.•The proposed FMEA method considers the attenuation effect in influence propagation.•The final risk priority of failure mode is computed recursively with the PageRank algorithm. Failure Mode and Effect Analysis (FMEA) is an efficient method for risk prevention and control, which has been applied to identify the potential risks and improve system reliability in various fields. Nevertheless, few attempts in previous research have been made to examine the impacts of the interactions among the failure modes on risk priority, which will influence the risk priority accuracy. To solve this problem, we propose a novel method to improve the conventional FMEA approaches. The proposed method not only considers the positive and negative influences of failure modes, but also the attenuation effect of such influences in the system. In addition, different from the previous FMEA approaches assuming that all failure modes play equally important roles in risk propagation, the new FMEA method considers the initial strength effect of failure mode on the risk propagation to ensure the accuracy of the risk priority. The final risk priority of a failure mode is computed recursively by the PageRank algorithm, which considers the effect of risk priority of other failure modes associated with this failure mode. Finally, to verify the effectiveness of the proposed method, we apply it to a case study of failure mode effect analysis for smart bracelets.