Human factors models for aviation accident analysis and prevention

Aviation is a complex system, and the investigation and modelling of aviation accident causation can suffer from being artificially manipulated into non-complex models and methods. This book addresses this issue by developing a new approach to investigating aviation accident causation through information networks, which centralise communication and the flow of information as key indicators of a system's health and risk. The book's new model offers many potential developments and some key areas are studied in this research, maintaining firm focus on the overall health of a system. Read more... Abstract: The investigation and modelling of aviation accident causation is dominated by linear models. This book addresses this issue by developing a new approach to investigating aviation accident causation through information networks. It presents a new model that offers many potential developments and some key areas are studied in this research. Read more... Content: Cover Contents List of Figures List of Tables About the Authors List of Abbreviations 1 Introduction 1 The Field of Human Factors 2 Objectives and Aims of the Book 3 Structure of the Book 2 Modelling a Dynamic World 1 Accident Causation Models 2 Runway Overrun at Bangkok (QF1) 3 Current Application of Human Factors in Aviation Accident Investigation 4 Incidents: A Tool for Proactive Safety 5 The Influence of Modern Technology Conclusions Summary 3 A Complex Approach to a Complex Scenario 1 Event Analysis of Systemic Teamwork (EAST) 2 The Kegworth Air Disaster 3 Data Gathering4 Analysis of Networks 5 Implications for Further Work and Limitations Summary 4 Development of a Study 1 The Importance of Centralising Communication 2 Expanding on the Idea of 'Ideal' Networks 3 Statistical Analysis of Networks 4 Selection of a Suitable Metric Conclusions 5 Extending the Potential of Information Networks: A Bayesian Approach 1 General Aviation: The 'Unprofessional' Genre? 2 Investigating General Aviation Accidents 3 Developing a Bayesian Information Network Approach 4 Outcomes, Limitations and Future Work Summary 6 Can We Validate Networks Derived from Incident Data Through Simulation? A Pilot Study1 Can a Validation Approach be Validated? 2 Methodology 3 Results 4 Other Results of Interest 5 Discussion Summary 7 Incidents versus Accidents: An Industrial Study 1 Safety Management Systems within Industry 2 'They've Rebadged it you Fool!' A Review of Best Practice in Aviation and Beyond 3 Is Risk Really = Severity × Frequency? 4 The 'Distance from Disaster' Model 5 Discussion of the Benefits and Limitations of Working in Industry 6 Conclusions and Further Work Summary 8 Conclusions 1 Book Contribution2 Tying Together Several Aspects of the Book 3 Developments and Directions for Future Work 4 Closing Remarks References Index The investigation and modelling of aviation accident causation is dominated by linear models. Aviation is, however, a complex system and as such suffers from being artificially manipulated into non-complex models and methods. This book addresses this issue by developing a new approach to investigating aviation accident causation through information networks. These networks centralise communication and the flow of information as key indicators of a system’s health and risk. This holistic approach focuses on the system environment, the activity that takes place within it, the strategies used to conduct this activity, the way in which the constituent parts of the system (both human and non-human) interact and the behaviour required. Each stage of this book identifies and expands upon the potential of the information network approach, maintaining firm focus on the overall health of a system. The book’s new model offers many potential developments and some key areas are studied in this research. Through the centralisation of barriers and information nodes the method can be applied to almost any situation. The application of Bayesian mathematics to historical data populations provides scope for studying error migration and barrier manipulation. The book also provides application of these predictions to a flight simulator study for the purposes of validation. Beyond this it also discusses the applicability of the approach to industry. Through working with a legacy airline the methods discussed are used as the basis for a new and prospective safety management system.