Discussion: Modeling In The Aviation Environment

Accident causation models have been around since the late 1800s. They helped identify hazards and explain the nature of accidents.
Read Chapter 2 – Modelling a Dynamic World (Attached). Then do the following in the assignment directions.

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Directions:

Review a model from the past or one that is used now and explain the theory of it.
Provide reasons for causation models (past and present) and their application to Human Factors.
Determine whether causation theories have made humans and/or organizations better at being proactive or predictive in accident prevention and in accident investigation.

About a page, APA with references

Chapter 2
Modelling a Dynamic World
1 Accident Causation Models
As Chapter 1 outlines, this project focusses on accident causation models and in particular their application to the field of Human Factors in aviation. In order to fully understand the current position and trends of accident causation modelling it is important to acknowledge the developments and history of the area and where there may be room for further investigation and work. This chapter aims to provide a comprehensive analysis of the history and development of models and where opportunities and validation for this project arise.
The next section begins with an aviation accident case study. This is then referred to at salient points of the chapter in order to maintain a rooted discussion. It is appropriate to look at the history of accident investigation models by way of illustrating them with a contemporary accident case study.
2 Runway Overrun at Bangkok (QF1)
At about 22:47 local time on 23 September 1999, a Qantas Boeing 747-438 aircraft registered VH-OJH (call sign Qantas One, en route from Sydney to London) overran runway 21 Left (21L) while landing at Bangkok (Don Mueang) International Airport, Thailand. The aircraft landed long and aquaplaned due to the runway being affected by water following very heavy rain.
The first officer was the handling pilot for the flight. The crew elected to use the ‘normal’ company practice configuration for the approach and at various stages during the approach to runway 21L, the crew were informed by air traffic control
Introduction Literature Review
Applying the Approach to
Industry (British
Airways SMS)
Conclusions
Development of a Complex
Network Approach
Validation Study (Flight Simulator)
Application of a Complex
Network Approach
Extending the Mathematical
Model (Bayesian Approach)
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Human Factors Models for Aviation Accident Analysis and Prevention26
that although there was a thunderstorm and heavy rain at the airport, visibility was 2½ mi/4 km (or greater).
At 22:44:53, the tower controller advised that the runway was wet and that a preceding aircraft (which landed at approximately 22:40) reported that braking action was ‘good’. As the aircraft descended through the 200 ft/60 m point, it started to deviate above the 3.15° glideslope, passing over the runway threshold at 169 kt at a height of 76 ft/ 23 m. Those parameters were within company limits but both high and fast. When the aircraft was approximately 10 ft/3 m above the runway, the captain instructed the first officer to go-around. As the first officer advanced the engine thrust levers, the aircraft’s main wheels touched down and the captain immediately cancelled the go-around by retarding the thrust levers, without announcing his actions. This resulted in confusion among the flight crew and reverse thrust was not selected or noticed to be absent during the landing run. The aircraft came to rest some 720 ft/220 m after the end of the stopway with its nose resting on an airport perimeter road. The aircraft sustained substantial damage during the overrun. None of the 3 flight crew, 16 cabin crew or 391 passengers reported any serious injuries (ATSB 2001).
Single Perception Theory
1890s The birth of modern research into accidents and causation is mostly attributed to the work of Bortkiewicz (1898). He concluded, from limited studies, that accidents occur at random and are therefore inexplicable. This view luckily did not restrain further research into accidents but instead opened the gates for years of investigation, conjecture and argument.
1910s and 1920s The majority of the work and investigation into accidents was at first set with a pivotal view of a single event perception whereby an accident or incident is regarded as a solitary event for which there must be a solitary cause. The job of an air accident investigator was to find this cause and, by eliminating it, stop an accident from recurring. Elements of the idea of a ‘single event’ remain, and mistaken use of the concept still occurs in work with aviation or other complex systems. However, it was soon realised that these environments spawn much more complex interactions between human–human, human–system and system–system components. This view of accidents also allowed for a blame culture to flourish, in that a party was seen as responsible – as a ‘cause’ of the ‘event’. An accident had to have someone or something at fault, to blame, so that what had happened was not purely an ‘act of God’ that could not be explained. This rather simplistic view and the work of, for instance, Greenwood and Woods (1919) from the Industrial Fatigue Research Board (IFRB) gave rise to the ‘accident proneness’ model. This focussed solely on the individual (rather than the system) and came to dominate the research and accident reduction exercises for the first half of the twentieth century.
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Modelling a Dynamic World 27
Further work within the IFRB and clinical studies of reactions, coordination and distraction, among other elements, concluded that accident proneness existed. It was considered related to nervous instability and poor aestheto–kinetic coordination (Farmer and Chambers 1926 and 1929). The uncritical acceptance of such an accident proneness model by the community at the time is almost fully attributed to this work. This view persisted for many years, although it can be seen that other work, such as domino theory, was already being developed, exposing the shortfalls of the current theory. Indeed, studies continued long after this time, examining the concept and working around the broad theory base of accident proneness in individuals. For example, in their 1988 study, Mohr and Clemmer find no real evidence for a proneness that is measurable or useful in accident causation analysis and conclude that ‘it is unlikely that overall injury rates in the workplace can be effectively reduced by screening out workers with excessive numbers of injuries’ (Mohr and Clemmer 1988: 127). This work illustrates the shortfalls of this model of accident investigation and so highlights the limits of application to our Qantas Flight 1 Accident Case Study (QF1) If accident proneness were the case, then the pilots should have been involved in other incidents prior to and following on from this event. These ideas cannot be substantiated given the evidence. This view also suggests that these people can be selected out and, therefore, that all accidents can be prevented by removing the accident-prone individual, at the selection or at the training stage, or after any incident has occurred. This is now, almost universally, accepted as a flawed theory. Dekker (2006) describes this ‘Bad Apple Theory’ as the ‘Old View’ and contends that safety progress was made mainly from technological advances and not as the result of the application of these theories. Thus, further models were needed to attempt to explain accident causation.
The main problem with the simple explanation of single perception theories, other than the realisation that more complex interactions occur, is that it assumes an innate replicability in incidents. If a ‘cause’ can be removed, then the accident could not happen again. Were this applied to QF1 and the event investigated in the 1920s, the pilots could be sacked and so the incident should not recur. This does not address any of the real issues and would have a devastating effect on morale and reporting behaviour were it enacted. The inherent fact is that accidents are viewed, now, at least, as being so complex that many different ‘causes’ could have produced an incident. It is often very difficult to identify a certain cause or produce an effective barrier to similar accident types. The single event perception is very much suited to the type of investigation predating Human Factors influence, as that conclusive ‘part’ of an aircraft, etc. could often be found and blame attributed to structural facets of the system. However, a systems view had to be developed and adopted.
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Human Factors Models for Aviation Accident Analysis and Prevention28
2.2 Domino Models and their Development: The Demise of ‘Proneness’?
1930s and 1940s In his book Industrial Accident Prevention (1931), Herbert William Heinrich elaborated for the first time on his domino theory of industrial accidents. For the first time in Human Factors literature, accidents were attributed to a sequential chain of events rather than a single causal factor (normally an employee). In order to illustrate this Heinrich used the idea of a series of dominoes falling over, causing the final event.
It is fundamental to this model of accident causation that Heinrich labelled each of the dominoes with causes that may lead to an accident. It can be contended that this resulted in the basis for modern accident causation models.
Heinrich’s first domino was entitled ‘Social Environment and Heredity’. This referred to the personality traits that are believed to be inherited, or the social environment that the worker is immersed in, influencing the likelihood of that worker being involved in an accident. This, in particular, echoes elements of accident proneness theory whereby internal facets of a human contribute towards accidents regardless of external factors. This, in a way, shows a development in accident proneness rather than a complete deviation, but the other dominoes bring in factors that were being discussed in all the research of those times.
Second, and linked through the chain of events basis of the theory, is the ‘Fault of Person’. This refers to the effect a worker’s life (as an outside influencer) is having on events such as family problems, fatigue, and so on. This includes flaws developed in the context of the social environment and the system in which the worker operates. This is a significant drawing together of ideas that external influences on an individual and accident causation are as significant as internal ideas of proneness, if not more so. Today this is still an important area in the investigation of accidents and incidents. These ‘soft issues’ are often easy to gain from those involved in an incident or accident on a surface level. It can be contended that approaching Human Factors via the ‘soft issues’ of family life and social life allows the industry to merely tick a box and not truly understand the more complex facets of system interaction with humans at all levels. However, referring again to QF1, had the event occurred in the 1930s there would at least have been some form of defence for the flight crew. For the first time in an investigation, outside influences would be considered and from this came the potential for changes to regulations, training and standards.
The second domino was also developed in Heinrich’s later expansions to include the actual expression ‘Mistake’ as a result of these personal factors. The third domino illustrates Heinrich’s direct cause of accidents/incidents. This domino was called either an ‘Unsafe Act’ or ‘Unsafe Condition’. The very idea that this domino is required in order to knock over the fourth, ‘Accident’, shows that Heinrich postulated that one or both of these must be present for an accident to occur. This model was the first to really develop the importance of behaviour on influencing safety and accident causation and Heinrich felt that this third domino was the most
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