Objective: The objective of this study was to enhance the existing system hazard analysis (SHA) technique by introducing the concepts of human and automation reliability quantification as well as fuzzy classification of system risks. These enhancements led to formulation of a new overall system risk-reliability score. Background: Many system safety analysis methods focus on individual physical component failure. Some human reliability analyses (HRA) consider human-automation interaction in determining system failure rates. There is no system safety analysis technique that quantifies the impact of human and automation reliability on the risk of hazard exposure. Method: Classification of the probability and severity of hazard exposure is typically made in terms of linguistic rather than numerical variables. Fuzzy sets are applicable for transforming linguistic classifications to numerical quantities. We focused on using fuzzy sets to define overlapping bands of system risk exposure with reference to the hazard risk categories defined in MIL-STD 882B. Fuzzy sets were also used for human-automated system reliability classification. Results: Introduction of human and automation reliability assessment in the SHA allows for definition of a system risk-reliability modeling space. The enhanced SHA (E-SHA) technique yields a mishap risk index, which is projected based on a composite assessment of human-automated system reliability at the time of operation. The E-SHA was compared with one of the most advanced HRA techniques. Conclusion: The E-SHA technique supports broader safety control recommendations and provides comparable, if not more detailed, results than prior systems safety and HRA techniques.