Research history, development, and progress in human factors aviation

Aviation & Human Factor

Aviation

"The history of the development and progress of Human Factors in aviation, highlighting areas of significant change"

Development in Aviation field is an essential element from defense prospective of any country. Advancement in assembly of an aircraft is always a result of some human error in handling. Error handling while pilot is operating an aircraft is an unrecoverable action in some cases. Human handling for safety of aircraft, preventive measures while operating an aircraft, regular maintenance for identifying errors in machinery and many other factors must be incorporated while training is given to pilots. Rate of damages and disasters also depends on human psychology. Quick action in tragedies and failure of aircraft is a primary part of training.

Table of Contents

Introduction

Aircraft Accidents

Human factors in Organization

Human Error and Human Factor Models

Aviation Mishap Analysis

High Risk in Human Aviators Problems 12

Beginnings of maintenance human factors research 13

Review of Human Factors Issues 16

Safety 16

Cooperation / Competition 17

Communication and coordination 18

Judgmental Bias 20

Mixed Equipage 21

Regulations related to Human Factor in Aviation 22

Some Current Aircraft Accident Reduction Methods 23

Risk Management 23

Threat and Error Management (TEM) / Line Operations Safety Audit (LOSA) 24

Actor Network Theory 24

Prospective Analysis / Spiral Development 25

Fault Tree Analysis (FTA) 25

Conclusion 26

References 27

"The history of the development and progress of Human Factors in aviation, highlighting areas of significant change"

Introduction

Aviation hazards are mostly caused either by human error or environmental conditions. One example of environmental conditions can be the cloudy or stormy weather. If the pilot is not experienced and properly trained to handle the aircraft in such weather there is possibility of an accident. Kapoor (2006) also concluded, "Maintenance error is a crucial factor in aircraft accidents" (p.4).

Aircraft accidents are the result of a chain of events that may begin with maintenance errors (Al-Amoudi, 1998). Al-Amoudi used data from the airline aircraft industry to test his hypothesis that changes within training, communications, safety, and human physiology can lead to reduced aviation maintenance technician errors. Al-Amoudi found that if the airline aircraft maintenance department addressed human factors, reduced maintenance errors will be prevented one in five times.

Human factor is behavior of a person and reaction to the environment while facing any situation. Global air transportation system officials rely on high-quality aircraft maintenance to provide safe, reliable aircraft (Dhillon & Liu, 2006). Errors among aircraft mechanics are of particular concern to the regulatory agencies and aviation organizations in nations participating in transportation system. Human factors (environmental, physiological and psychological) are widely recognized as the precursors to mechanic error, and ultimately, to maintenance related aircraft accidents (Baron, 2009; Hackworth, 2007; Hobbs & Williamson, 2003). Current essay is aimed at exploring the history of the development and progress of Human Factors in aviation. In particular the essay will focus on highlighting areas of significant change.

Below is a brief discussion of the aviation hazards, aircraft accidents, human error and human factor models followed by a detailed discussion on the development and progress of Human Factor in aviation

Aircraft Accidents

The aviation industry is one of the most highly regulated industries worldwide (Brong, 2002). The NTSB defined aircraft accidents as:

"An occurrence associated with the operation of an aircraft which takes place between the time any person boards the aircraft with the intention of flight and all such persons have disembarked, and in which any person suffers death or serious injury, or in which the aircraft receives substantial damage" (Electronic Code of Federal Regulations, 2010).

Federal Aviation Regulations concerns "the design, manufacturing, and certification of aircraft, including their engines and other systems, the certification of airlines, and the certification of personnel who directly affect the safe operation of the aircraft" (Reynolds, 2005, p.59). Continual oversight of repair station operations as well as maintenance, repair, and overhaul facilities performing aircraft maintenance procedure is impressive to ensuring safety standards are enforced. Lu (2006) stated, "Accidents indicate a continuing demand to improve safety; but as the same time, most airline operate with a 'red-ink' balance sheet" (p. 114). Problems within the airline industry are highlighted by the occurrence of aircraft accidents and serve to focus attention on areas of concern (Murray, 2009).

Maintenance errors have been to blame for a significant percentage of aircraft accidents (Baron, 2008). Human error causes 55% of aviation catastrophes (Hughes, 2009). Errors can be contamination of equipment, corrosion of aircraft systems or components, failure of aircraft systems or components, or any other aircraft discrepancy resulting from a maintenance action. Root causal factors can contribute to airline aircraft maintenance errors. Errors have been attributed to six root causes, including the shortage of performance quality control and management oversight, not adhering to standard aircraft maintenance practices or procedures, erroneous FAA data, inadequate knowledge and training, hurried service, and ignorance of standard operational procedures (Lu, 2006). These factors can result in various error-related overcomes or events.

UN-airworthy dispatch of aircraft into service between the years 1996 through 2000 accounted for 40% of the maintenance error related events. Of these occurrences, 16% of the time the maintenance error did not result in a negative effect, and the error was simply found and corrected at a later maintenance check (Patankar & Taylor, 2003). Baron (2009) noted "deviations from approved procedures continue to be a leading cause of maintenance-related aircraft accidents" (p.2). Maintenance errors are a direct result of human error and "it has been estimated that human error is involved in 70% of aircraft accidents" (Hobbs & Williamson, 2003, p.187).

Human factors in Organization

Human factors in resource management are challenging and difficult to handle. Mangers prefer human factor specialists to help their employee. This step gives a positive impact on the growth of an organization. The performance of employees gets a big push and it will rise above. Error handling will decrease in this case. In terms of aviation the error or mistake is unavoidable as there is no recovery from the loss occurs due to this activity.

Mistakes are done my customers in every aspect of their business. In organization we suffer loss of money due the wrong investment. We also suffer from variety of things like damage to property. Property damage can be the end result of natural disaster, some external sources wants to disturb your business. Thieves steel your system. These factors can be handling and in future. Either we over come from these losses, recover the theft material or whatever the condition. But the loss during aviation is the life of the human.

Life of human is unrecoverable factor. We can only take preventive measures. But after the loss the thing can't recover any more.

Human Error and Human Factor Models

A great deal of the literature has been devoted to recording the chronological development of human error and human factors models and taxonomies. While many of the current models describe only a narrow view of one aspect of human error, Rasmussen (1983) suggests that rather than a single quantitative model, an overall qualitative model of human performance, supported by more detailed quantitative models that represent aspects of human functions and limiting properties, would be more effective in system design. Much like the definitions of systems engineering provided by Kossiakoff and Sweet and cognitive systems engineering provided by Amalberti and Sarter, Corker and Gore (2002) identified an important aspect of human error modeling as "the interaction among the physical and cognitive structures in completing complex jobs." They further suggest that understanding the processes that generate will lead to a better overall comprehension of the underlying concepts of human performance which, in turn, will allow for the development of better human performance predictive tools (Corker and Gore, 2002). Kahneman and Tversky provide three heuristics that humans employ in making decisions in an environment of uncertainty:

"Representativeness" -- employed when human is required to use judgment to decide if an event or object is linked to another class or process;

Availability of instances of scenarios -- employed when human is required to asses the frequency of a class or the plausibility of a development; and Adjustment from an anchor -- employed in a numeric prediction when relevant shows the values that are available (Kahneman and Tversky 1974, p. 1131)

A robust and comprehensive compilation of human performance model descriptions in the literature was provided by Anderson (2002). While their work was mostly confined to the air traffic management domain, they classified human performance models and human error omits in the following categories (Andersen, 2002, p.12-19).

Task-based taxonomies -- "classification systems that state what happened in terms of human error mode";

System-oriented taxonomies -- "similar to task-based taxonomies in that they also determine what failures occurred, but also consider maintenance errors or other such events that may have effect on the incident";

Communication system models -- "models and taxonomies that deal with the communication aspect of the error such as communication medium, method, expectations or sender/receiver, and so forth;

Information processing models-"a set of models used extensively in the field of psychology and human factors, central to which is the method that humans internally process information input, filter, and apply judgment/decision making";

Symbolic processing models -- "in contrast to information processing models, these systems view the human in a more cognitive manner as a symbol manipulator and having reference mental models of the environment with which to decide how to act";

Situational awareness approach -- "widely applied to the aviation field, this model examines the human's awareness of key elements into understanding, and extrapolation of their effect on the future";

Control system models -- "systems that use control theory concepts to describe performance";

Perceptually-centered models-"a variant of control system models, they are a combination of control theory and symbolic processing theory";

Signal detection theory -- "system view the human as a signal detector in an environment of "noise" and, hence, subject to false alarms or rejection of actual information";

Error of commission models -- "approaches that attempt to examine unintended acts of humans and relate interactions in a highly complex system";

Violation taxonomy -- "models that deal with situations in which the human operator intentionally overlooks a rule";

Cognitive simulations -- "computerized systems that are based on symbolic processing theory models intended to mimic human cognitive performance particularly in complex decision-making environments";

Contemporary accident theory -- "approaches that focus on the nature of the accident, they imply that there is no single solution to most accidents and recognize a larger "organizational level" influence and culture";

Other domain taxonomies -- "specific and specialized approaches such as those developed for specific purposes with the nuclear power industry"; and Other transportation related approaches -- "systems utilized in the maritime, flight crew or air traffic control domains dealing specifically with transportation modes" (Andersen, 2002, 12-19).

Aviation Mishap Analysis

The previous section described some of the theoretical perspectives of human error and human error modeling. This section describes the application of these systems to accident investigation -- specifically aviation mishaps. Several examples of initiatives to apply human error theory to accident investigation and mitigation are described in the literature. A few are presented below;

A combined government and industry effort undertaken in the U.K. developed the Human Factors Investigation Tool (HFIT). Gordon and Means (2005, 147) describe the intent of this tool was to, "improve investigation of the human factors causes of accidents in the offshore oil and gas industry." HFIT incorporated four types of human factors information to include "(a) the action errors occurring immediately prior to the incident, (b) error recovery mechanisms, in the case of near misses, (c) the thought processes which lead to the action error and (d) the underlying causes" (Gordon and Means, 2005, 147).

In their study of workplace accidents and fatalities in Australia between 1982 and 1984, Cairns, Feyer, and Williamson (1997) found evidence to link error types committed in an accident to pre-existing work practices. This reinforced the idea of the organization itself having an influence on accidents.

In their work on MIDAS (the Man-Machine Integration Design and Analysis System _ a tool developed to model human performance), Gore and Jarvis (2005) developed a fatigue behavioral model mathematically defined by the total error values for an action as a contribution of pre-task fatigue and within-task fatigue, and calculated by evaluating the maximum values of the probability of error, time penalty of the task, and a quality penalty.

High Risk in Human Aviators Problems

There are certain professional matters that are considered while the aviation flies in a safe manner and do their job effectively. Safety is the first priority to consider and implement in a proper manner.

The percentage of human error in aviation is almost 75%. The more than half percentage contribution forces us to think about its serious concerns. The major problem is when pilot is stressed and not able to fly in a required manner. The communication factor holds a primary factor in this concern. The pilot and instructor are friendly enough to share their problems, understand each other and have the comfortable atmosphere between each other to tell what they feel. The case in which pilots are not able to fly in a proper manner and stressed out, they should tell their instructor about the present condition of their mind. Pilots are not forced to fly the plane when they are not stable mentally. This instability may be the result of personal problems and other issues.

There is huge research on human factor and human errors in aviation including environmental studies and research related to the behavior and performance of pilots and crew members. Pilot in this context is the central character and there is great risk of accidents if the pilot is not appropriately trained or has ability to make right decision on right moment. Reaction of a pilot in emergency landing matters and shows his performance. As it is part of training that if a pilot is sure about the plane is going to crash and there is no other way out, then he must land a plane where the number of population is less. Places like sea, mountain and less populated areas.

The pilots are discouraging themselves to ask for help from successful aviators. It is generally thought the sign of fear. The pilot is scared they may be given a psychological treatment to reduce their fear and consider as this treatment is only to help them out from this situation. It is not to declare them as a sick but it is way to help them.

The stress factor is mainly due to the personal problems. These problems are the cause of medical conditions; the person is drunk, family issues, arrival of new child. These are the factors which are closely integrated with family issues.

Problems are also related the qualification is not on the current basis.

Beginnings of maintenance human factors research

All through the history of aviation, the research on human factor has been developed and stressed with aircraft design, aviation organizations and the regulation of pilots. Wells and Rodriguez (2003) described that during the initial time of aviation development, 80% of aircraft accident were due to mechanical failure and the reason behind the remaining 20% were human errors; yet, till the 1980s human error were responsible for almost 80% of accidents. This development was due to the improved technology and better aircraft consistency. Thus with the passage of time the focus of aviation security was shifted from officials to human errors. Mechanics were not considered much as pilot error rapidly became an accepted reason for majority of accidents (Taylor & Pantankar, 2001). As a result the regulatory authorities centered enforcement solely on the pilot workforce in the United States and United Kingdom (Edkins, 2002). Unluckily, by the 1990s, many prestigious drifts in mechanic amendment emerged and drew attention to the directive of human factors in the mechanic personnel.

A significant case of human error appeared in 1988 when an Aloha Airline Boeing 737 underwent an extravagant structural breakdown when the fuselage composition adjacent to the passenger compartment came off aircraft during flight. Mechanics had continually unsuccessful to notice progressive cracking of the structure. Although pilots successfully landed the aircraft, the unsavory reputation of this incident was the reason that almost all the upcoming research included this event as an instance of maintenance faults. Followed by Aloha incident was an EMB-120 crash at Eagle Lake, Texas. This incident happened because the mechanics released the aircraft for flight without a complete maintenance. In this case, mechanics had disassembled one portion of the tail and after that did not reassemble before permitting the aircraft for flight. The aircraft made a successful flight from Houston to Eagle Lake. While coming back, full with passengers on the way to connect flights in Houston, the aircraft broke up in flight. Similarly in the year 1955, an Atlantic Southeast Airlines EMB-120 crashed because of the failure of mechanics to identify advancing corrosion damage around the linking ring of a propeller blade. After the 31 minutes of flight, a propeller blade parted from the engine. The crew of the aircraft tried a forced landing but failed and aircraft crashed.

The bad reputation of the Aloba event caused a striking move in aviation safety. Photos of passengers still in their seats that were exposed by the missing fuselage were more powerful images of an incident related to human error. Though human factor bylaws were already present for pilots, the prototype change was utilized to center on the issue of aircraft mechanics and their errors. In the 1990s the research on human factor in aviation shifted from exploring the reasons behind maintenance errors to why these mistakes were frequently being made.

Initial research on human factor in aviation mostly used high profile, disastrous incidents to reveal the hazard posed by aircraft maintenance in the non-existence of human factors programs. Whilst the research examined every incident in detail and highlighted errors so that other maintainers may avoid, they were not able to show the quantitative extent of the issue as regards accident rate related to maintenance or to produce trend analyses to forecast future rates. With almost 187% increase in air travel, the incidents related to maintenance also increased (Fogatry, 2004). Highlighting the outcomes of maintenance approaches no longer sufficed because researcher became aware that there was a need for more thorough approaches to the problem.

Turning from reviewing the high profile incidents, the researcher centered on categorizing accidents related to maintenance so as to analyze the most repeated errors for the development of more focus on corrective measures (Aslanides, 2007; Majumdar, 2009). Yet some other researcher centered to develop trend with the use of the ASRS database of self-reported (by the mechanic) maintenance errors (Lattanzio, 2008; Patankar, 2003). Until 2003, researchers started to focus on the advantages of human factor programs for aircraft mechanics, but were not able to offer evidence for its support because organizational leaders till then had not implemented any human factor program on a large scale. After the preliminary heave in the 1990s, interest in maintenance human factors rapidly dissipate as inquisitive literature into the issue lessened dramatically after 2001 and almost disappeared after 2003 (Dhillon & Liu, 2006)

Review of Human Factors Issues

Safety

Roberts (1990) stated that complexity, tight coupling and interdependence of functions within a system puts them at high risk of catastrophe. The effective organizational solution to mitigate the high risk in the system has been to provide various levels of redundancies. In future ATM system the complexity, coupling and interdependence of functions will increase as the pilots will bear responsibility of strategic conflict resolution by actively negotiating the changes in the trajectory. The air traffic controllers are likely to act as a second line of defense and will resolve conflicts in cases where pilots are not successful in conflict resolution.

However, ATCos are posed with a difficult task. As Moray, Lee and Hiskes (1994) pointed out; questions of when to intervene and what is the best intervention in a partially autonomous system have theoretical and practical problems. This problem is best described by Dekker and Woods (1999).

"Management by exception turns out to trap human controllers in a double bind, where intervening early seems appealing but is difficult to justify and carry out. Late interventions are just as difficult since controllers will have to take over in the middle of potentially challenging and deteriorating situation."

Research has indicated that there are fundamental differences between how and when pilots and air traffic controllers resolve conflicts. Pilots seem to prefer late resolution with vertical maneuvers as compared to early intervention and lateral maneuvers by air traffic controllers. The issue of whether pilots will be able to successfully resolve conflicts at all times is highly debatable. Wickens, Mavor, Parasuraman and McGee (1998) state that the organizational psychology of negotiations and group behavior is not very well understood. This assertion is further supported by Dingus, Jahn, Horowitz, and Knipling (1998), who note that even in a simple case of negotiation as to who has right of way on a stop sign can be fairly complicated. The authors cite that 30% of vehicle crashes happen in intersections that are crossing path type (crossing straight paths at 90 degree angle) and have a stop sign. Although in this cases there exists well defined rules of the road, sometimes they are just not followed. Many times a crash is caused because a false assumption made about the other vehicle's planned action.

Cooperation / Competition

It can be contemplated that a distributed air traffic management system will lead to an environment that will be partly cooperative and partly competitive. Wickens (1998) noted that it is not clear how homogenously pilots will achieve the appropriate balance between safety and efficiency. As safety is paramount, it will foster collaboration; however the pressure to conform to flight schedule in trailing airline economy has huge potential to foster competition. As noted by Beatty, Hsu, Berry, and Rome (1999), state that every minute added to the flight time en route can cause a ripple delay effect and can add up to 13 minutes of delay on the subsequent leg thus driving the cost upwards. From an economic standpoint this will always invoke a competitive nature in the pilots. Furthermore, there is only one preferred maneuver (vertical ascending) to resolve a conflict with regards to cost as demonstrated by Krozel and Peters (1997). They note that altitude maneuvers are most economical followed by heading maneuvers, and speed change maneuvers. Altitude maneuvers are presumed favorable for two reasons. First, the vertical separation requirement is less stringent than the horizontal separation requirements, thus making altitude maneuvers easier to achieve. An aircraft needs only 1000 ft vertical separation, compared with 5 NMI (30380 ft) horizontal separations. If one considers only the clearance distance required by each maneuver, the altitude maneuver is 30 times less demanding. The second advantage for altitude maneuvers is that they are largely conservative. The aircraft gains potential energy while climbing, which it in turns uses during descent. In comparison, the turning aircraft increases its load factor, which increases drag considerably and consumes energy. Also, the detour made by turning aircraft has no subsequent benefit. It has also been noted that vertical maneuvers are preferred from the standpoint of passenger safety (Westrenen and Groeneweg, 2003) as they can better handle vertical acceleration in altitude change as compared to side forces in lateral maneuvers.

Communication and coordination

Research on the role of communication in the free flight has revealed an increased need for air to air and air to ground communication between pilots and controllers (Mackintosh et al., 1998). Endsley (1997) reported that air to ground communication (pilots sharing their intent with controllers) is essential for controllers in order for them to maintain situational awareness. Duley, Galster, Masalonis, Hilburn and Parasuraman (1997) noted that information about delineation of separation responsibility needs to be effectively communicated for safety reasons. This is especially true, in cases where the resolution has to be generated by ATCos (Andrews and Hollister, 1997).

Also, it is likely that future voice communication may be replaced by data link communication. A data link is a messaging system that transfers text messages back and forth. Studies conducted to understand the impact of using data link have reported an increase in collaboration between controllers and pilots in a data link environment (Farley, Hansman, Amonlirdviman, & Endsley, 2000); however other data has shown that pilot initiated communications decline with data link usage (Lozito, McGann, & Corker, 1991). Furthermore, the nature of communication changes from synchronous to asynchronous and Wickens et al. (1998) note that this can complicate the conflict resolution process.

In a distributed system the effectiveness of problem solving extends beyond the formal channels of communication, and is also dependent on interaction between the individuals. Heath and Luff (1991) emphasized the importance of interpersonal interaction while attempting to study the impact of distributed systems in London underground train control room. One of their key findings was that controllers, rather than relying on each other for formal information exchange, often overhear and monitor each others' tasks to carry out their jobs. Similarly, Hutchins and Klausen (1990) studied interactions between the crewmembers in an aircraft cockpit. The authors emphasized the importance of inter-subjective understanding of interaction in distributed problem solving. According to them, inter-subjectivity supports efficient kinds of communication and it permits human actors to intend and find meaning in many non-verbal and verbal aspect of the behavior which go beyond literal utterances. Riley (1992) states that one of the drawbacks of the data link is that implicit information like urgency level and illocutionary forces cannot be conveyed by data link and hence it does not support the transmission of implicit information. It is noted above that in a distributed system many a times the operators overhears the communication of coworker to perform their job. This sort of situation exists even in the ATM environment. The supervisor, data side and the handoff controller often listen to the conversation of the radar side controller to form a shared mental model (Bowers, Blickebsderfer and Morgan, 1998). With the introduction of data link, new tools might be required to form a common situational awareness as the information will no longer be available to the colleagues through the conventional listening in activity.

It is not clear as to how much information sharing or communication is required between pilots and air traffic controllers in conflict resolution process. On one hand researchers have suggested that there is an increased need of communication and on the other hand some studies have demonstrated that the conflict resolution can be performed in absence of any communication between pilots with help of decision aids.

Judgmental Bias

It is reported that there is an apparent mismatch of expectations and biases between the pilots and air traffic controllers in their attempt to solve conflicts. One reason commonly cited is that controllers and pilots have different resolution strategies, due to their fundamentally different working goals. Pilots behave in more "aircraft centric" manner as they tend to choose the resolution strategy that is optimal for their own flight and least disruptive on their flight plan and efficiency. Controllers on the other hand tend to behave in more "airspace centric" manner as they focus on entire chunk of airspace and choose resolution that is has minimal effect on the flow of traffic through their sector when making their decisions. Furthermore, Sperandio (1978) notes that controllers working strategy may change with the traffic situation. For example when the traffic density is high the controller's may relax some performance criteria to accommodate for increase in workload. Sperandio reports that there is a relation between efficiency and traffic density. With increase in the sector traffic the controllers tend to relax the efficiency criteria and start using a less sophisticated strategy. For example instead of calculating optimal flight paths for the aircraft at low sector count they would use a stereo-typical flight path (non-optimal) at high sector count.

Coming back to the issue of differences between pilots and ATCos, with regards to how they solve conflicts. In a recent experiment, it was reported that pilots and controllers have different styles of solving conflicts (DiMeo, 2002) with respect to maneuvering style, timing of action and separation distance. Controllers solve the conflict earlier than pilots and use more altitude and heading clearances, while pilots use more speed and heading changes. Pilots also tend to use multiple and complicated strategies (for example speed and heading changes together) as compared to controllers. Controllers preferred a greater separation distance then pilots during conflict resolution.

Xu, Wickens and Rantanen (2004) reported that pilots have decision bias in conflict detection. For example a distance over speed bias has been demonstrated to exist in pilots (a distance over speed bias such that two aircraft viewed farther apart and converging rapidly perceived as less risky than two aircraft that were closer to each other and converging at a slower rate, even though the time until a conflict occurred were identical).

Mixed Equipage

It is envisioned that it is unlikely that airlines will equip all its fleet to with decision support automation so that they can participate in advanced ATM concepts as the high cost incurred in equipping the aircraft might not be justifiable. Thus not all aircraft will be able to carry out the separation assurance responsibility on their own and will have to be managed by ATCos. Hence, there will be a mix of free flying and non-free flying aircrafts.

The impact of mixed equipage on ATCo's (Air traffic controller) performance has raised some serious issues and questions (Corker, Fleming, and Lane, 1999; Metzger, Rovira, & Parasuraman, 2003). For example, how successful are controllers in maintaining separation between aircraft mix? How well can they allocate their attention differentially to the traffic mix? And what is the effect of proportions of various types of aircrafts in the sector? Metzger, Rovira, & Parasuraman (2003) studied the effect of traffic mix and automation with regards to controller's performance and workload. They reported degradation in air traffic controller's conflict detection performance in the mixed equipage environment. However, the detection performance improved when the controllers were provided an automated conflict alert.

Regulations related to Human Factor in Aviation