Human reliability analysis in aviation accidents: A review

Abstract

Verbatim from Semantic Scholar. Not paraphrased, not summarized.

In the civil aviation sector, human factors is the primary cause of many safety incidents. Aircraft flying, maintenance, and operations are the major tasks that are heavily dependent on professionals; thus, they are subject to human error probability. Human reliability analysis (HRA), which can evaluate human state and managing risk, has been developed over the years to identify, predict, and reduce human failures throughout aircraft operating procedures. Different generations of HRA tools have been developed to quantify the risks that are associated with safety accidents, including such as the Human Error Assessment and Reduction Technique, Technique for Human Error Prediction, Standardized Plant Analysis Risk Human Reliability Analysis, Cognitive Reliability and Error Analysis Methods, and Bayesian Network (BN). However, little is known about how these approaches are applied in aviation safety. This review aimed to systematically examine the current status of research on HRA in aviation accidents. A total of 13 studies were included and encompassed the studies of the first, second, and third generalizations of HRA alone or in combination with other methods (e.g., Improved Analytics Hierarchy Process, Functional Resonance Analysis Methods, Human Factor Analysis and Classification System, and Fault Tree Analysis). Results revealed that the third-generation HRA with BN was frequently used, showing great application potential for flight safety risk prevention and reduction. In the future, testing other third-generation HRA models driven by data in the field of airworthiness is necessary.

Authors

• Steven Tze Fung Lam
• Alan H.S., Chan

Keywords

• Engineering