Reliability engineering: Old problems and new challenges
By Enrico Zio. Reliability Engineering & System Safety, 2009
866 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/6db1ec19b4698937958224bcd8a275c6b739836c
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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Changhua Hu
- Wenbin Wang
- Benoît Iung
- Donghua Zhou
- Xiaosheng Si
- Gabriela Medina-Oliva
- Joseph Homer Saleh
- Zhaoyi Xu
Citations in the corpus
- Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas (2012, background): “…to be modeled in a system for assessing dependability and maintenance aspects are: - the complexity and size of the system (large-scale systems) (Zio, 2009), - the temporal aspects (Labeau et al. 2000), - the integration of qualitative information with quantitative knowledge on different…”
- The future of risk assessment (2018, background): “As a result, today's systems are not only required to be reliable but must also be able to recover from disruptions [224,230].”
- Risk assessment and risk management: Review of recent advances on their foundation (2016, background): “…steps (in line with what one finds in standards such as ISO 310 0 0 and most risk analysis text books (e.g. Aven, 2015a; Meyer & Re-niers, 2013; Zio, 2007a ): i. Establish context, which means for example to define the purpose of the risk management activities, and specify goals and criteria.…”
- Machine Learning for Reliability Engineering and Safety Applications: Review of Current Status and Future Opportunities (2020, background): “In a previous review work of reliability engineering [18], the author summarized the progress to date in the field and highlighted some of its challenges.”
- Remaining useful life estimation - A review on the statistical data driven approaches (2011, background): “…to RUL There have been excellent review papers over the last few decades on maintenance related issues, maintenance optimisation and modeling techniques and fault diagnostics, see for example Cho and Parlar (1991), Reinertsen (1996), Scarf (1997), Wang (2002a), and Zio (2009) to name a few.”