Recent natural and human-made disasters, mortgage derivatives crises, and the need for stable systems in different areas have renewed interest in the concept of resilience, especially as it relates to complex industrial systems with mechanical failures. This concept in the engineering systems (infrastructure) domain could be interpreted as the probability that system conditions exceed an irrevocable tipping point. But the probability in this subject covers the different areas that different approaches and indicators can evaluate. In this context, reliability engineering is used the reliability (uptime) and recoverability (downtime) indicators (or performance indicators) as the most useful probabilistic tools for performance measurement. Therefore, our research penalty area is the resilience concept in combination with reliability and recoverability. It must be said that the resilience evaluators must be considering a diversity of knowledge sources. In this thesis, the literature review points to several important implications for understanding and applying resilience in the engineering area and The Arctic condition. Indeed, we try to understand the application and interaction of different performance-based resilience concepts. In this way, a collection of the most popular performance-based resilience analysis methods with an engineering perspective is added as a state-of-the-art review. The performance indicators studies reveal that operational conditions significantly affect the components, industry activities, and infrastructures performance in various ways. These influential factors (or heterogeneity) can broadly be studied into two groups: observable and unobservable risk factors in probability analysis of system performance. The covariate-based models (regression), such as proportional hazard models (PHM), and their extent are the most popular methods for quantifying observable and unobservable risk factors.
The report is organized as follows: After a brief introduction of resilience, chapters 2,3 priorly provide a comprehensive statistical overview of the reliability and recoverability domain research by using large scientific databases such as Scopus and Web of Science. As the first subsection, a detailed review of publications in the reliability and recoverability assessment of the engineering systems in recent years (since 2015) is provided. The second subsection of these chapters focuses on research done in the Arctic region. The last subsection presents covariate-based reliability and recoverability models. Finally, in chapter 4, the first part presents the concept and definitions of resilience. The literature reviews four main perspectives: resilience in engineering systems, resilience in the Arctic area, the integration of “Resilience, Reliability, and Recoverability (3Rs)”, and performance-based resilience models
