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Training to Facilitate Adaptive Capacity in Automated Systems
Capt. Shem Malmquist, FRAeS
While automation has often been touted as the source of the improvements in aviation safety during the past 30 years, evidence shows that the improvements are more likely due to better component reliability resulting in fewer unusual problems. The unfortunate side effect of this increase in component reliability is that pilots today have less exposure to unusual circumstances outside of the well-defined and scripted problems in training scenarios. The high reliability has masked a potentially dangerous mix. Less exposure to real-world complex problems reduces our ability to find ways to cope with unexpected problems. Simultaneous to this, the modern aircraft include integrated modular avionic systems that can result in cascading and often very confusing failure scenarios, accompanied by even more confusing alerts. Despite this, training of many skill sets continues to be reduced such that pilots are no longer well versed in understanding aerodynamic principles, their aircraft systems, to include advanced flight control systems and the hidden traps in automated weather avoidance systems such as multi-scan radars. Meteorology, never well trained, continues to be mostly ignored. While more senior pilots may still retain skill sets to overcome the reduction in exposure to complex problems, they are leaving the industry through attrition and the newer generation has no way to obtain the skill sets necessary to manage complex failures on their own.
Utilizing MIT’s System Theoretic Process Analysis (STPA), this presentation provides some insights into how we might modify our current training to improve pilot adaptive capacity while utilizing the current technology, as well as explore how we might design future automated systems to better utilize human skill sets.
A Systems Engineering Approach to Safety Performance Indicators and Accident Causality
Capt. Shem Malmquist, FRAeS
John Thomas, Ph.D., Research Engineer/Scientist, Massachusetts Institute of Technology
As the technical and non-technical systems we are building become increasingly complex it is becoming increasingly difficult to identify true safety performance indicators. Similarly, it difficult to isolate a single or even a few obvious root causes among the abundance of direct and indirect factors that contribute to modern accidents. There is also a growing recognition of the need to better understand human behaviors that contribute to accidents. Unfortunately, there are few methods to systematically pose and answer these questions and it can be easy to simply treat human error as a conclusion rather than a potential indication of deeper trouble. In addition, the importance of systemic factors, organizational issues, and other high-level factors is widely accepted but there are still few systematic and rigorous methods that can be applied broadly across the entire sociotechnical system including interconnected technical, human, organizational, regulatory, and other issues.
To address these and other issues, a new accident analysis method known as STAMP (System Theoretic Accident Model and Processes) has been developed at MIT. This methodology provides a comprehensive framework and a step-by-step process to systematically analyze complex sytems, to pinpoint subtle but critical issues like systemic factors that present an “accident waiting to happen”, and to identify important unanswered questions that may otherwise be overlooked. In this presentation we will provide a summary of the STAMP methodology as it applies to identifying leading indicators and aircraft accident investigation.
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