Comprehensive hybrid framework for risk analysis in the construction industry using combined failure mode and effect analysis, fault trees, event trees, and fuzzy logic

The nature of the construction industry is characterized by many risks and uncertainty inherent in every phase of the project life cycle. Risk management, therefore, is essential for a construction project to succeed in fulfilling its project objectives. In conventional event-tree analysis, the probability of the risk event, the probability of failure/success of different mitigation strategies, and the consequences of different paths must be assessed to allow for quantitative event-tree analysis. However, conducting quantitative event-tree analysis, especially in construction projects, entails several difficulties attributed to the lack of sufficient data. To overcome this challenge, this paper presents a comprehensive framework in which experts can use linguistic terms rather than numerical values to conduct event-tree analysis and calculate the expected monetary value (EMV) of risk events. The proposed framework is based on combining failure mode and effect analysis (FMEA), fault trees, event trees, and fuzzy logic. This paper allows experts to express themselves linguistically to calculate the EMV of risk events, which is more appropriate for the construction domain. In addition, this paper introduces a comprehensive framework for risk management that combines three well-known techniques in reliability engineering in a novel way that considers the often subjective quality of risk-related data. The application of fuzzy logic provides an effective tool to handle subjectivity in the construction domain. The proposed framework is implemented in the form of two software tools entitled Risk Criticality Analyzer and Fuzzy Reliability Analyzer. To validate the framework, a case study is presented and the EMV is calculated using the proposed approach. The result of the proposed approach is then compared to the result obtained using Monte Carlo simulation, demonstrating that the proposed framework gives similar results to Monte Carlo simulation but provides the advantage of allowing experts to express themselves linguistically, making the proposed framework more practical and easier to apply in the construction domain.