Abstarct: Сritical infrastructure refers to an asset, a system, or a part of it necessary to maintain society’s vital functions, health, safety, security, or economic or social welfare. Moreover, its disturbance due to lack of maintenance, improper operation, or errors in the design phase will significantly impact society. For years, risk management has been recognized as the only fundamental way to improve the safety of infrastructure systems against disasters. This approach focuses on designing sturdy systems that are able to withstand disasters using preventive and protective programs. However, recent events such as the COVID-19 pandemic have shown that most infrastructure systems cannot withstand all possible disruptions. Therefore, attention has shifted from robust design to resilient design that focuses on preparedness, response, and recovery. Resilience is an emerging concept whose application has increased significantly in managing engineering systems. In order to have an effective resilience management, frst, an estimation of the system resilience should be undertaken. However, a lack of historical data and limited information are major challenges for system resilience estimation. The main reason is that most data collection systems are not designed for resilience assessment. Moreover, the available study dealing with resilience assessment have been used different indices to quantify the resilience of critical infrastructures including, robustness, recoverability, etc. These indices can be affected in a complex way by different factors such as operational conditions, protective practices, the recovery process, logistic process, etc. However, the available resilience studies are not so detailed regarding identifying and quantifying these influencing factors. Therefore, this thesis aims to develop and apply a practical methodology to estimate total resilience index (TRI) baxsed on the combination of expert judgment and fuzzy set theory. By adopting this methodology, factors influencing resilience can be modeled effectively. The presented methodology adopts resilience concepts, including reliability, maintainability, organizational resilience, and PHM system effciency indices to estimate the TRI. This method can emerge the strengths and weaknesses of system resilience either in technical (hard resilience) or organizational (soft resilience) areas. It helps managers to recognize those systems’ areas that are more sensitive and require more attention. Consequently, they can follow a more detailed assessment and implement improver strategies. To show how the proposed methodology can be used in real cases, it was applied to the main fan system of Tabas Coal mine. In Tabas coal mine, the fan house of the mine includes three parallel main fans, called ventilation banks, with each bank containing two series axial fans. In this study, the type of disruption was defined as the fans' bearing failure. According to the results, the main fan restorative capacity is weaker than absorptive and adaptive capacities. Inadequate budgeting and low supportability for the system are the reasons for this weakness. Among the indicators affecting the reliability and maintainability indices of the main fan of the mine, the status of the operational conditions index is more sensitive than others. Moreover, it was found that in the field of personnel related to the main fan of the mine, not much attention is paid to maintaining and transmitting experience as well as learning from past experiences. In the field of organizational resilience index, each of the four generic indicators affecting the organizational resilience index has a weak condition and the ownership sense index is more critical than the other indicators. In this thesis, some attempts were made to provide appropriate strategies to improve the status of identified weaknesses. However, providing more accurate and useful solutions requires more extensive field investigation. Therefore, to improve the resilience of the main fan, the root causes of the identified weaknesses through more detailed field studies can be recognized. Then appropriate strategies can be adopted to improve their condition.