Serious Accidents and Human Factors—Breaking the Chain of Events Leading to an Accident

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There is growing concern globally over issues of aviation safety. Awareness of previous failures and their causes is one of the most important factors in determining risks and hazards in any new operational systems. This requires experience of accidents and failures across a broad spectrum of complex systems.

Every accident occurs as a result of a chain of errors, and if one of the links making up that chain can be broken, the accident might be prevented – and becomes merely an incident. If you collect detailed data from a range of incidents, relating to how they occurred, and develop a consistent method for analysing that data, you can create a potentially valuable resource to assist in accident prevention.

Serious Accidents and Human Factors proposes an original and structured approach to accident prevention. In an interesting and readable collection of accounts of major accidents, drawn mainly from the aviation industry, Masako Miyagi investigates incident reports analytically and reveals the critical information hidden therein that could avert a full-blown accident or disaster. She applies an innovative analytical technique – multi-dimensional analysis of incident reports (MAIR), using a particular model (Quantification Method III) to validate the results and focus upon individual components identified within the causal chain of events that precede an accident. She advocates wider acceptance and use of IRAS (Incident Report Analysing System), ideally administered by a neutral and independent body, to help prevent accidents not only in aviation but in relation to all complex systems, such as nuclear power plants.

Serious Accidents and Human Factors offers aviation industry personnel, as well as those involved more generally with safety, risk assessment, and accident prevention in other industries, a comprehensive understanding of the accident causation chain, events contributing to that chain, and a method for identifying and eliminating causal factors in a proactive way.