Human Error Mitigation System in Aviation

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Human Error Mitigation System in Aviation

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Introduction

Apparently, human errors or maintenance errors contribute immensely to most of the faults that cause aircraft accidents. Moreover, pilot error has been a major concern in the cause of a number of air crashes (Salas & Maurino, 2010). As a result, there has been a major alarm in the training of pilots and the maintenance crew as they have been blamed for some of the general aviation crashes or rather accidents. The statistics are still disturbing irrespective of the fact that technology has evolved immensely in that it has been able to alert the pilots of a possible collision hence reducing the number of collisions; human error is still a disturbing problem in the aviation industry (Joint Aviation Authorities (Europe), 2007).

Besides, there are a number of factors that have been known to be the cause of most human error and consequent plane crashes, collisions or poor landing. Some of the factors include inefficient or poor communication between the control tower and the pilots, sometimes the pilots may get fatigued because of the long voyages thus missing small but crucial details that could avert aviation disasters and also, in adequate training (Dhillon, 2007). In addition, sometimes distractions occur or even inattentiveness that results to dire consequences. Apparently, the Aviation sector is calling for extensive retraining to some of its pilots and maintenance crew to ensure that the issue of human error is mitigated once and for all (Harris et al, 2006).

Moreover, in order to mitigate these threats, a wider scope of research is said to fall on cockpit design, human interaction, the understanding of the complex aviation software and training of both the maintenance team and the pilots (Dismukes, 2009). There have been suggestions that the use of high-tech motion stimulators will see to it that emergencies are handled better. In addition, the automation of most cockpit command and automated systems will see to it that fatigue for the pilots are mitigated. However, training and mentorship of pilots is an aspect that has been given keen interest to ensure that human error is mitigated (Salas & Maurino, 2010).

Interestingly, human error cannot be confined to the pilots and maintenance engineers alone but also to flight-deck systems and the control tower too. However, critical emphasis still falls on the inappropriate response to troubling trends before an accident occurs (Dhillon, 2007). Besides, the inability to realize and recognize failures in automation has been some of the disturbing human errors in the aviation industry that could be averted if the necessary actions are taken. Other maintenance errors include engine failures, or even any other mechanical damages (Dismukes, 2009).

Human Error in Cockpit Design or Pilot Error

Apparently, in dealing with human errors in the cockpit, there are two training systems that have proved very effective in addressing the issue. Apparently, Cockpit Resource Management (CRM) and the Line-Oriented Flight Training (LOFT) are some of the systems that have proven very effective in mitigation of human error (Salas & Maurino, 2010). Apparently, LOFT involves the simulation of a flight by the airline crew before the actual flight takes place. The small problems encountered by the pilot demand for a collaborative teamwork approach so as to avoid a catastrophe during the actual flight. The simulation is used for test and study purposes in determining the actual errors and problems that may occur during an actual flight (Harris et al, 2006).

On the other hand, CRM is a system that has been embarked to empower the subordinates and to ensure that the superiors listen. The system stresses leadership, prompt and appropriate decision making, and sanity in judgement, management of stress, authority delegation and creation of situational awareness before and during a flight. Apparently, the system ensures that subordinates can be able to air their views and report on anything that they think might cause harm to the flight. Apparently, the crew may detect something odd with the plane during a flight but since the captain is in charge, some of them do not brook any interference from the juniors and as a result avoidable catastrophe due to human error could occur (Dismukes, 2009).

Taking into consideration that man is to error and error is to man, the same saying cannot be given any chance in the aviation industry. The reason behind it is because the chance of survival in case of any airplane malfunction tends to zero; a flight has to be done perfectly well (Salas & Maurino, 2010). As a result, in a bid to mitigate human and design errors, the Human Error Identification System or Technique (HEI/HET) has to be applied. Apparently, HET was developed to aid in the prior and on-time identification or design errors that may put the flight or the functioning of the airplane at risk. It is through this system that the certification of flight-decks is made (Harris et al, 2006).

Apparently, HET is easy to learn and implement as its starting point is a task analysis that is hierarchical. The system counterchecks about twelve design modes in a bid to determine the most liable one to lead to credible errors (Harris et al, 2006). The analysis is very idealistic in that the error is well-described and the potential outcome is outlined. In addition, a related task to mitigate the error is described and in case the likelihood of the error is very high, then it is rated as “fail”. Besides, the tasks to be executed in a bid to mitigate the errors are analyzed in depth (Dismukes, 2009).

Therefore, the incorporation of LOFT, CRM and HEI would definitely improve the human error mitigation in the cockpit and the aviation in general. Some of the most effective HEI system methods in mitigation and prediction of human error include HEIST, SHERPA and HAZOP. The three methods are effective in prediction of the correct errors that a pilot or the maintenance team may make in the aviation industry. Therefore, the use of HEI is an effective approach to human error management as the issue is the one that has contributed immensely to most of the aviation accidents that have happened globally (Dhillon, 2007).

Current Safety Status and Philosophy in dealing with the System

Taking a look at Systematic Human Error Reduction and Prediction Approach (SHERPA) in the mitigation of human error in the cockpit, the method has its approach from a hierarchical analysis (Joint Aviation Authorities (Europe), 2007). Therefore, the system uses error taxonomy in determining the specific tasks to take for a given error mode. Apparently, each task step is classified in regards to the SHERPA taxonomy of human error. Moreover, the system advocates for an number of approaches in dealing with human error detection. The first one is the Action; this refers to description of a given form of error (Salas & Maurino, 2010).

Secondly, the consequences that may result from the in-attendance of the error are stipulated as well as any possible steps that could be taken in a bid to return the normal function of the airplane in case the error happens (Kanki, Helmreich & Anca, 2010). Thirdly, records are made on potential designs or remedies that may mitigate the errors by rating the criticality of how effective the remedy is, get rated on a low, medium and high basis. Arguably, it SHERPA is a very effective HEI method that provides a comprehensive and reliable error prediction platform. Besides, potential errors are exhaustively analyzed in detail (Salas & Maurino, 2010).

However, when it comes to Human Error Hazard and Operability Study (HAZOP), it is used in the assessment of engineering risk as well as the assessment of the process design audit via the use of guidewords in identification of credible errors (Dhillon, 2007). Apparently, the guidewords are for example, more than, less than, not done, later than, sooner than and so on. Consequently, other factors about the error such as its description, cause, consequences and a remedy plan are recorded. Moreover, any remedial designs in respect to the error are recorded. Besides, the process is simple and has proven very effective under the HEI system even though it may be time consuming, it has proven effective in the identification of human error (Joint Aviation Authorities (Europe), 2007).

Apparently, a good example is where a human error occurs in that the pilot forgets to enter a required new airspeed; this error gets recorded. Apparently, the consequence of the error is that the speed of the plane will increase instead of reducing as required; this consequence is also recorded (Horn, 2010). In addition, the cause of this consequence needs to get recorded and it is recorded as; the pilot and the crew usually have a high workload than required making them fatigued. Finally, a design improvement aimed at addressing the mitigation of the error is recorded and in this case the pilot may issue an auditory prompt warning to the pilot on the speed of the airplane (Dismukes, 2009).

Lastly, the HEI system has a very important method in the mitigation of human error through error-identification approach; the Human Error Identification in Systems Tool (HEIST). In this method, HEIST uses eight tables to identify human errors via well-designed error-prompt questions (Salas & Maurino, 2010). The questions guide the analyst in the detection of potential error and they identified errors are recorded. However, even though the error-identifier prompts are very effective in human error identification in the cockpit and the whole aviation setup in general, they are all effective in the aviation context. However, HEIST has been used extensively in human error identification and the results have been impeccable (Dhillon, 2007).

Current Philosophy and the system Protection

Taking an example of a landing task the HEI system and the SHERPA method are mostly used by pilots in the prediction of possible errors in the autoland system (Joint Aviation Authorities (Europe), 2007). Apparently, this method is very effective in aviation as its error taxonomy is cognitively effective to the aviation industry and suitable to the tasks that pilots carry out in the cockpit. The reason behind it is that there are many actions involved in the management of the whole plane as well as ‘checks’ that if missed, could result to catastrophic experiences (Kanki, Helmreich & Anca, 2010).

Comparing the Selected Programs to other Programs

However, the use of the three HEI methods is very effective in ensuring that error identification is simplified in the aviation industry in order to avoid accidents that may be preventable. On the other hand, when the HEI system is compared to the LOFT and CRM systems, it has proven to be more effective than the two (Dhillon, 2007). Moreover, it is easy to implement but it takes a longer period than the latter two. As for the case of LOFT, the frequent flight simulations are necessary in error identification. However, HEI has three cognitive methods that can be applied concurrently and make error detection easier, faster and cheaper (Kanki, Helmreich & Anca, 2010).

Supported Recommendations on System Improvement

In a bid to reduce some of these serious accidents and human errors that are consequently dire, remedial training on pilots to enhance their training skills which have apparently been eroded as a result of the high rate of automation in the cockpit. The problem with automation is that there is very little physical engagement of the pilot with the system and their attention tends to be impeded (Horn, 2010).

On the other hand, testing of the scheduled pilots before a flight is made is very ideal as such issues as aborted landing, proper takeoffs, proper landing and engine failure detection can be determined so as to assess the capability of the pilot and the maintenance team before the actual flight is made. The importance of these tests will be to determine if the crew meets the set standards to manage the flight as well as mitigating possible errors as soon as possible (Salas & Maurino, 2010).

Moreover, a continued use of the HEI system in human error identification in the aviation industry would be an awesome approach in getting results. Apparently, HEI is a simple method that is easy to apply (Horn, 2010). However, the SHARPA method is the best approach to use as it has high accuracy in error prediction and identification (Harris et al. 2006). Apparently, if the use of HEI system is affected in the aviation industry, there is high probability that aviation accidents and incidents will reduce significantly and if well-implemented, they will be totally eradicated. Investing in the human resource is very important in the aviation sector as automation alone cannot be relied on in error identification (Dhillon, 2007).

Conclusion

The success of human error in maintenance and pilot errors, the HEI system has proven to be very effective both in terms of efficiency and in terms of cost effectiveness. The SHERPA is a method that has been effective in detection of human errors both in maintenance and in the cockpit as it has high precision (Dhillon, 2007).

References

Dhillon, B. S. (2007). Human reliability and error in transportation systems. (Springer e-books.) London: Springer.

Dismukes, K. (2009). Human error in aviation. Farnham, Surrey: Ashgate.

Harris, Don, Stanton, N., Marshall, Andrew, Young, M., … Salmon, P. (2006). Using SHERPA to predict design-induced error on the flight deck. Elsevier.

Horn, K. P. (2010). Use of the C-27J fixed-wing aircraft for conducting Army mission critical, time sensitive missions in counterinsurgency operations. Santa Monica, CA: RAND.

Joint Aviation Authorities (Europe). (2007). JAA ATPL training. Frankfurt: Jeppesen.

Kanki, B. G., Helmreich, R. L., & Anca, J. M. (2010). Crew resource management. Amsterdam: Academic Press/Elsevier.

Salas, E., & Maurino, D. E. (2010). Human factors in aviation. Amsterdam: Academic Press/Elsevier.




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