Judgemental errors in aviation maintenance

Cognition, Technology & Work - Aircraft maintenance is a critical success factor in the aviation sector, and incorrect maintenance actions themselves can be the cause of accidents. Judgemental...     

Eradicating root causes of aviation maintenance errors: introducing the AMMP

This is the second of two papers in the area of aviation maintenance safety enhancement utilizing human error risk management in engineering systems methodology. The first focused on the retrospective analysis of human error in aircraft maintenance, where the impact of human reliability on aviation maintenance safety was investigated. The purpose was to explore the actual mechanisms of maintenance errors initialization and propagation, with the aim of identifying requisite characteristics for future solutions. This second part focuses on a prospective approach to proactive safety techniques that can be applied to the field. It builds on the findings from the previous work and introduces a proposed Aviation Maintenance Monitoring Process (AMMP); an integrated process that is to be collectively implemented by industry to proactively monitor existence of human error causal factors. These factors are typically pre-initiated during design practices, manufacturing processes, or at later stages due to organizational, individuals, or workplace conditions within maintenance, repair, and overhaul organizations (MRO). As a result, such causal factors can be gradually eliminated. This generic AMMP is based on user software built applying the fuzzy Analytic Network Process (fuzzy ANP) theory, with a database of a communal total of 870 assessment criteria designed within the software. The full process is validated practically in real world within industry.     

Greener aviation with virtual sensors: a case study

The environmental impact of aviation is enormous given the fact that in the US alone there are nearly 6 million flights per year of commercial aircraft. This situation has driven numerous policy and procedural measures to help develop environmentally friendly technologies which are safe and affordable and reduce the environmental impact of aviation. However, many of these technologies require significant initial investment in newer aircraft fleets and modifications to existing regulations which are both long and costly enterprises. We propose to use an anomaly detection method based on Virtual Sensors to help detect overconsumption of fuel in aircraft which relies only on the data recorded during flight of most existing commercial aircraft, thus significantly reducing the cost and complexity of implementing this method. The Virtual Sensors developed here are ensemble-learning regression models for detecting the overconsumption of fuel based on instantaneous measurements of the aircraft state. This approach requires no additional information about standard operating procedures or other encoded domain knowledge. We present experimental results on three data sets and compare five different Virtual Sensors algorithms. The first two data sets are publicly available and consist of a simulated data set from a flight simulator and a real-world turbine disk. We show the ability to detect anomalies with high accuracy on these data sets. These sets contain seeded faults, meaning that they have been deliberately injected into the system. The second data set is from real-world fleet of 84 jet aircraft where we show the ability to detect fuel overconsumption which can have a significant environmental and economic impact. To the best of our knowledge, this is the first study of its kind in the aviation domain.     

Helicopter maintenance error analysis: Beyond the third order of the HFACS-ME

In this paper a statistical analysis of a sample of 58 helicopter maintenance-induced safety occurrences is conducted to study helicopter accidents and incidents’ survivability and the severity distribution of such occurrences. Analysis is also carried out to identify helicopter main and sub-systems mostly exposed to maintenance errors and to determine various types of such errors. Expected inherent relations between rotorcraft components affected and types of associated maintenance errors are investigated. Human factors-based triggers of these accidents and severe incidents are explored. The concept of Specific Failures (SFs) that immediately precede each of such occurrences is introduced for more detailed representation of the last breached individual and organizational safety barriers. Root causes of these safety occurrences were then sought utilizing the Human Factors Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy with a refined focus on its third order categories’ list. The rotorcraft characteristics influencing individuals and organizational behaviours within Maintenance, Repair and Overhaul organizations (MROs) are discussed in the light of the root cause investigation results.

Relevance to industry

The study of human reliability within helicopter maintenance industry is waited to emphasise the understanding of causes and propagation mechanisms of maintainers' errors and their consequences on the overall aviation safety. Previous works often investigated maintenance errors and their roles in promoting aviation accidents of fixed-wing aircraft; this research is investigating the case of rotorcraft.     

The development of a model and simulation of an aviation maintenance technician task performance

This paper describes the model of an aircraft maintenance technician (AMT) behaviour working in a real world environment and the application of this model in a computer simulation. The model was derived from the combination of two existing models of cognition (SHELL and RMC/PIPE), based on the paradigm of an information processing system. The simulation structure was developed by transforming the model into an action-execution structure and implementing this model in a computer program based on an object-oriented programming language. An error generation system was coupled to a simple taxonomy of causal correlations between socio-technical and contextual factors operating in an environment defined by a comprehensive task analysis. The simulator can be applied to many aviation maintenance tasks to assist in the design of aviation maintenance training systems through the analysis of the interaction of performance influencing factors and possible AMT performances during the execution of normal maintenance operations. A number of sample outputs from the simulator show the potential of the results to assist in training development. A discussion is also made of other potential applications and the future directions the simulator structure can take.     

Human error and commercial aviation accidents: an analysis using the human factors analysis and classification system

OBJECTIVE: The aim of this study was to extend previous examinations of aviation accidents to include specific aircrew, environmental, supervisory, and organizational factors associated with two types of commercial aviation (air carrier and commuter/ on-demand) accidents using the Human Factors Analysis and Classification System (HFACS). BACKGROUND: HFACS is a theoretically based tool for investigating and analyzing human error associated with accidents and incidents. Previous research has shown that HFACS can be reliably used to identify human factors trends associated with military and general aviation accidents. METHOD: Using data obtained from both the National Transportation Safety Board and the Federal Aviation Administration, 6 pilot-raters classified aircrew, supervisory, organizational, and environmental causal factors associated with 1020 commercial aviation accidents that occurred over a 13-year period. RESULTS: The majority of accident causal factors were attributed to aircrew and the environment, with decidedly fewer associated with supervisory and organizational causes. Comparisons were made between HFACS causal categories and traditional situational variables such as visual conditions, injury severity, and regional differences. CONCLUSION: These data will provide support for the continuation, modification, and/or development of interventions aimed at commercial aviation safety. APPLICATION: HFACS provides a tool for assessing human factors associated with accidents and incidents.     

Investigating the use of moving windows to improve software effort prediction: a replicated study

To date most research in software effort estimation has not taken chronology into account when selecting projects for training and validation sets. A chronological split represents the use of a project’s starting and completion dates, such that any model that estimates effort for a new project p only uses as its training set projects that have been completed prior to p’s starting date. A study in 2009 (“S3”) investigated the use of chronological split taking into account a project’s age. The research question investigated was whether the use of a training set containing only the most recent past projects (a “moving window” of recent projects) would lead to more accurate estimates when compared to using the entire history of past projects completed prior to the starting date of a new project. S3 found that moving windows could improve the accuracy of estimates. The study described herein replicates S3 using three different and independent data sets. Estimation models were built using regression, and accuracy was measured using absolute residuals. The results contradict S3, as they do not show any gain in estimation accuracy when using windows for effort estimation. This is a surprising result: the intuition that recent data should be more helpful than old data for effort estimation is not supported. Several factors, which are discussed in this paper, might have contributed to such contradicting results. Some of our future work entails replicating this work using other datasets, to understand better when using windows is a suitable choice for software companies.     

Seasat-A: a retrospective

Abstract

This paper traces the highlights of the Seasat-A project from its earliest conceptual phases through the orbital operations phase. The primary objective of the project was to demonstrate the feasibility of remotely sensing fundamental oceanographic phenomena on a global, accurate, reliable and timely basis from an Earth-orbiting platform. The project successfully achieved its primary objective, in spite of a premature spacecraft failure, and thus provided a firm basis for the development of sensors for future ocean-observing space missions.     

On-board preventive maintenance: a design-oriented analytic study for long-life applications

With respect to the long-life missions associated with NASA’s X2000 Advanced Deep-Space System Development Program, reliability implies a system’s continuous operation for many years in an unsurveyed radiation-intense environment. Further, the stringent constraints on the mass of a spacecraft and the power on-board create unprecedented challenges on the means for achieving the ultra-high mission reliability. In this paper, we present an approach to on-board preventive maintenance which rejuvenates a system by letting system components rotate between on-duty and off-duty shifts, slowing down a system’s aging process and thus enhancing mission reliability. By exploiting nondedicated system redundancy, hardware and software rejuvenation are realized simultaneously without significant performance penalty. Our design-oriented analysis confirms a potential for significant gains in mission reliability from on-board preventive maintenance and provides to us useful insights about the collective effect of age-dependent failure behavior, residual mission life, risk of unsuccessful maintenance and maintenance frequency on mission reliability.     

Measure, error and intrinsic fuzziness: a mathematical study of vagueness

 An operative method is proposed to evaluate degrees of membership, in situations when imprecise observations are made in a repeated way. The procedure is developed for limited subsets of the real axis R, but can be extended to R ^N . The analysis of a special case in R² shows the existence of sets whose membership function does not become a characteristic function, even when the inaccuracy of sampling vanishes and the observations are made in absolutely precise way.     

Mixed-fleet flying in commercial aviation: a joint cognitive systems perspective

Previous research investigating work activities and cognition in multi-crew airline flight decks has used a joint cognitive systems approach. However, is this approach suitable when some components—such as pilots—physically shift between differing aircraft, or joint cognitive systems? A current practice within the airline industry, known as mixed-fleet flying (MFF), allows pilots to fly aircraft of slightly differing configurations within the same working roster. The assumption held by aviation authorities is that pilots are permitted to fly in MFF configurations as long as relevant training occurs. Based on a cognitive anthropological study on pilots flying the same aircraft type—with differing flight deck configurations—we demonstrate that there are two different joint cognitive systems at work as each system involves different functional systems. The aim of this paper is to extend certain aspects of the joint cognitive systems approach to enable an analysis of real-world issues like MFF.     

Investigating voice in action teams: a critical review

Cognition, Technology & Work - Team communication is considered a key factor for team performance. Importantly, voicing concerns and suggestions regarding work-related topics—also termed...     

Core task modelling in cultural assessment: a case study in nuclear power plant maintenance

This article aims at illustrating the use of core task modelling on a system level and attempts to show its relevance to cultural assessment. The methodology that was used in a case study consists of an iterative process of core task modelling, organisational culture research and organisational assessment. The case study was conducted in a nuclear power plant's (NPP's) maintenance department. The maintenance task, its goals, critical demands and the demands for the working practices were conceptualised by core task analysis. The organisational culture of the maintenance department was explored with interviews, a survey and workgroups. The results show three critical demands and three instrumental demands to be controlled on all levels in the organisation. The maintenance culture must support the activity of balancing between these distinct requirements. The core task model was used in assessing the characteristics of the maintenance culture. This was done through analysing the unity of the personnel's conceptions concerning the organisation, its tasks, goals and values. The relevance of this approach to organisational development is discussed.     

Probability-based multiple-criteria optimization of bridge maintenance using monitoring and expected error in the decision process

In the context of limited financial resources under uncertainty, an important challenge is to introduce monitoring concepts in the general assessment, maintenance and repair frameworks of highway bridges. Structural health monitoring (SHM) provides new information on structural performance. As the monitoring duration increases, additional information becomes available. The knowledge of the structure is more accurate, but the monitoring costs are greater. Based on the accuracy of monitoring, different decisions can be made. These decisions involve uncertainties, and, consequently, are expressed in terms of probabilities. A probability-based approach for multiple criteria optimization of bridge maintenance strategies based on SHM is proposed. A measure of the error in the decision process, based on monitoring occurrence and duration, is proposed. Optimal solutions are obtained considering multiple criteria such as expected failure cost, expected monitoring/maintenance cost, expected accuracy of monitoring results, and ensuring that all constraints are satisfied.     

Visual misperception in aviation: glide path performance in a black hole environment

OBJECTIVE: We sought to improve understanding of visual perception in aviation to mitigate mishaps in approaches to landing. BACKGROUND: Research has attempted to identify the most salient visual cues for glide path performance in impoverished visual conditions. Numerous aviation accidents caused by glide path overestimation (GPO) have occurred when a low glide path was induced by a black hole illusion (BHI) in featureless terrain during night approaches. METHOD: Twenty pilots flew simulated approaches under various visual cues of random terrain objects and approach lighting system (ALS) configurations. Performance was assessed relative to the desired 3 degrees glide path in terms of precision, bias, and stability. RESULTS: With the high-ratio (long, narrow) runway, the overall performance between 8.3 and 0.9 km from the runway depicted a concave approach shape found in BHI mishaps. The addition of random terrain objects failed to improve glide path performance, and an ALS commonly used at airports induced GPO and the resulting low glide path. The worst performance, however, resulted from a combination ALS consisting of both side and approach lights. Surprisingly, novice pilots flew more stable approaches than did experienced pilots. CONCLUSIONS: Low, unsafe approaches occur frequently in conditions with limited global and local visual cues. Approach lights lateral of the runway may counter the bias of the BHI. The variability suggested a proactive, cue-seeking behavior among experienced pilots as compared with novice pilots. APPLICATION: Visual spatial disorientation training in flight simulators should be used to demonstrate visual misperceptions in black hole environments and reduce pilots' confidence in their limited visual capabilities.