Application of Human Factors Analysis and Classification System (HFACS) to UK rail safety of the line incidents

Minor safety incidents on the railway cause disruption, and may be indicators of more serious safety risks. The following paper aimed to gain an understanding of the relationship between active and latent factors, and particular causal paths for these types of incidents by using the Human Factors Analysis and Classification System (HFACS) to examine rail industry incident reports investigating such events. 78 reports across 5 types of incident were reviewed by two authors and cross-referenced for interrater reliability using the index of concordance. The results indicate that the reports were strongly focused on active failures, particularly those associated with work-related distraction and environmental factors. Few latent factors were presented in the reports. Different causal pathways emerged for memory failures for events such a failure to call at stations, and attentional failures which were more often associated with signals passed at danger. The study highlights a need for the rail industry to look more closely at latent factors at the supervisory and organisational levels when investigating minor safety of the line incidents. The results also strongly suggest the importance of a new factor – operational environment – that captures unexpected and non-routine operating conditions which have a risk of distracting the driver. Finally, the study provides further demonstration of the utility of HFACS to the rail industry, and of the usefulness of the index of concordance measure of interrater reliability.     

Associations between task,training and social environmental factors and error types involved in rail incidents and accidents

Rail accidents can be understood in terms of the systemic and individual contributions to their causation. The current study was undertaken to determine whether errors and violations are more often associated with different local and organisational factors that contribute to rail accidents. The Contributing Factors Framework (CFF), a tool developed for the collection and codification of data regarding rail accidents and incidents, was applied to a sample of investigation reports. In addition, a more detailed categorisation of errors was undertaken. Ninety-six investigation reports into Australian accidents and incidents occurring between 1999 and 2008 were analysed. Each report was coded independently by two experienced coders. Task demand factors were significantly more often associated with skill-based errors, knowledge and training deficiencies significantly associated with mistakes, and violations significantly linked to social environmental factors.     

Operator error and system deficiencies: Analysis of 508 mining incidents and accidents from Queensland, Australia using HFACS

Historically, mining has been viewed as an inherently high-risk industry. Nevertheless, the introduction of new technology and a heightened concern for safety has yielded marked reductions in accident and injury rates over the last several decades. In an effort to further reduce these rates, the human factors associated with incidents/accidents needs to be addressed. A modified version of the Human Factors Analysis and Classification System was used to analyze incident and accident cases from across the state of Queensland to identify human factor trends and system deficiencies within mining. An analysis of the data revealed that skill-based errors were the most common unsafe act and showed no significant differences across mine types. However, decision errors did vary across mine types. Findings for unsafe acts were consistent across the time period examined. By illuminating human causal factors in a systematic fashion, this study has provided mine safety professionals the information necessary to reduce mine incidents/accidents further.     

Routes to failure: analysis of 41 civil aviation accidents from the Republic of China using the human factors analysis and classification system

The human factors analysis and classification system (HFACS) is based upon Reason's organizational model of human error. HFACS was developed as an analytical framework for the investigation of the role of human error in aviation accidents, however, there is little empirical work formally describing the relationship between the components in the model. This research analyses 41 civil aviation accidents occurring to aircraft registered in the Republic of China (ROC) between 1999 and 2006 using the HFACS framework. The results show statistically significant relationships between errors at the operational level and organizational inadequacies at both the immediately adjacent level (preconditions for unsafe acts) and higher levels in the organization (unsafe supervision and organizational influences). The pattern of the 'routes to failure' observed in the data from this analysis of civil aircraft accidents show great similarities to that observed in the analysis of military accidents. This research lends further support to Reason's model that suggests that active failures are promoted by latent conditions in the organization. Statistical relationships linking fallible decisions in upper management levels were found to directly affect supervisory practices, thereby creating the psychological preconditions for unsafe acts and hence indirectly impairing the performance of pilots, ultimately leading to accidents.     

Analytical HFACS for investigating human errors in shipping accidents

Despite the innovative trends in marine technology and the implementation of safety-related regulations, shipping accidents are still a leading concern for global maritime interests. Ensuring the consistency of shipping accident investigation reports is recognized as a significant goal in order to clearly identify the root causes of these accidents. Hence, the goal of this paper is to generate an analytical Human Factors Analysis and Classification System (HFACS), based on a Fuzzy Analytical Hierarchy Process (FAHP), in order to identify the role of human errors in shipping accidents. Integration of FAHP improves the HFACS framework by providing an analytical foundation and group decision-making ability in order to ensure quantitative assessment of shipping accidents.     

Human and organisational factors in maritime accidents: Analysis of collisions at sea using the HFACS

Over the last decade, the shipping industry has implemented a number of measures aimed at improving its safety level (such as new regulations or new forms of team training). Despite this evolution, shipping accidents, and particularly collisions, remain a major concern. This paper presents a modified version of the Human Factors Analysis and Classification System, which has been adapted to the maritime context and used to analyse human and organisational factors in collisions reported by the Marine Accident and Investigation Branch (UK) and the Transportation Safety Board (Canada).     

A non-probabilistic prospective and retrospective human reliability analysis method — application to railway system

The paper describes a method to analyze human reliability. It defines human reliability as a degradation function related to deviations of both human behavioral state and system state due to this behavior. The method is called ACIH, a French acronym for Analysis of Consequences of Human Unreliability. It is a non-probabilistic approach, which aims at identifying both tolerable and intolerable sets of human behavioral degradations, which may affect the system safety. The corresponding scenarios of degradations are characterized by a behavioral model of unreliability including three main factors: acquisition related factors, problem solving related factors, and action related factors. Both prospective and retrospective analyses are taken into account to specify error prevention tools. They are applied to the railway system.     

The contribution of human factors to accidents in the offshore oil industry

Accidents such as the Piper Alpha disaster illustrate that the performance of a highly complex socio-technical system, is dependent upon the interaction of technical, human, social, organisational, managerial and environmental factors and that these factors can be important co-contributors that could potentially lead to a catastrophic event. The purpose of this article is to give readers an overview of how human factors contribute to accidents in the offshore oil industry. An introduction to human errors and how they relate to human factors in general terms is given. From here the article discusses some of the human factors which were found to influence safety in other industries and describes the human factors codes used in accident reporting forms in the aviation, nuclear and marine industries. Analysis of 25 accident reporting forms from offshore oil companies in the UK sector of the North Sea was undertaken in relation to the human factors. Suggestions on how these accident reporting forms could be improved are given. Finally, this article describes the methods by which accidents can be reduced by focusing on the human factors, such as feedback from accident reporting in the oil industry, auditing of unsafe acts and auditing of latent failures.     

Application of a human error framework to conduct train accident/incident investigations

Accident/incident investigations are an important qualitative approach to understanding and managing transportation safety. To better understand potential safety implications of recently introduced remote control locomotive (RCL) operations in railroad yard switching, researchers investigated six railroad accidents/incidents. To conduct the investigations, researchers first modified the human factors analysis and classification system (HFACS) to optimize its applicability to the railroad industry (HFACS-RR) and then developed accident/incident data collection and analysis tools based on HFACS-RR. A total of 36 probable contributing factors were identified among the six accidents/incidents investigated. Each accident/incident was associated with multiple contributing factors, and, for each accident/incident, active failures and latent conditions were identified. The application of HFACS-RR and a theoretically driven approach to investigating accidents/incidents involving human error ensured that all levels of the system were considered during data collection and analysis phases of the investigation and that investigations were systematic and thorough. Future work is underway to develop a handheld software tool that incorporates these data collection and analysis tools.     

Misconceptions of human factors concepts

Abstract

Like many scientific topics, Human Factors, and Ergonomics concepts are susceptible to being misunderstood by people unfamiliar with the subject matter. Most of the time these misunderstandings are harmless, like when a safety poster within a work setting encourages employees to 'overcome complacency'. This misunderstanding of complacency suggests it is a motivational aspect of human behaviour correctable with encouragement, whereas the human factors approach to overcoming complacency would be to evaluate how task design could diminish the destructive consequences of unexpected changes within a routine setting. No harm comes from the message within the safety poster, other than some wasted ink and paper, but misconceptions among particular audiences can eventually result in dire consequences for the human operator. This paper presents recent evidence that the concepts are being misapplied by casual consumers of human factors, particularly in the aftermath of accidents within complex systems, in ways detrimental to the core mission of improving the well-being of the human operator. Later, because this special issue presents new ways to demonstrate value via return on investment, practical efforts we can take to overcome such misconceptions are suggested.     

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents.     

Accident investigation reporting deficiencies related to organizational factors in machinery space fires and explosions

Careful accident investigation provides opportunities to review safety arrangements in socio-technical systems. There is consensus that human intervention is involved in the majority of accidents. Ever cautious of the consequences attributed to such a claim vis-à-vis the apportionment of blame, several authors have highlighted the importance of investigating organizational factors in this respect. Specific regulations to limit what were perceived as unsuitable organizational influences in shipping operations were adopted by the International Maritime Organization (IMO). Guidance is provided for the investigation of human and organizational factors involved in maritime accidents. This paper presents a review of 41 accident investigation reports related to machinery space fires and explosions. The objective was to find out if organizational factors are identified during maritime accident investigations. An adapted version of the Human Factor Analysis and Classification System (HFACS) with minor modifications related to machinery space features was used for this review. The results of the review show that organizational factors were not identified by maritime accident investigators to the extent expected had the IMO guidelines been observed. Instead, contributing factors at the lower end of organizational echelons are over-represented.     

核电厂系统人因工程学的应用研究

文章阐述了核电厂人因工程学应用现状，并介绍了应用在核电厂的人的可靠性分析的方法，提出了应用人因工程学改进核电厂可靠性与安全性的一些建议。     

Integrating human factors into process hazard analysis

A comprehensive process hazard analysis (PHA) needs to address human factors. This paper describes an approach that systematically identifies human error in process design and the human factors that influence its production and propagation. It is deductive in nature and therefore considers human error as a top event. The combinations of different factors that may lead to this top event are analysed. It is qualitative in nature and is used in combination with other PHA methods. The method has an advantage because it does not look at the operator error as the sole contributor to the human failure within a system but a combination of all underlying factors.     

Elderly drivers and their accidents: the Aging Driver Questionnaire

The Manchester Driver Behavior Questionnaire (DBQ) was included as part of a questionnaire survey of 1989 drivers aged 50 or over. Previous research has differentiated three main types of aberrant driver behavior: errors, lapses and violations. Each of these has different psychological origins, and different implications for road safety interventions [Reason et al., 1990. Ergonomics 33, 1315–1312]. It has also been shown that, using a full age-range sample of drivers, reported violations were statistically associated with accident involvement, whereas errors and lapses were not [Parker et al., 1995a. Ergonomics 38, 1036–1048; Parker et al., 1995b. Accident Analysis and Prevention 27, 571–581]. Although factor analysis of the DBQ responses of this sample produced five factors, the original three-way distinction was preserved. However the pattern of relationships between factor scores and accident involvement was different. Relatively high scores on the error factor and the lapse factor were predictive of involvement in an active accident, while passive accident involvement was associated with high scores on the lapse factor.     

Killer crashes: Fatal road traffic accidents in the UK

Road traffic accidents are responsible for over 3000 deaths per year in the UK, according to Department for Transport (2004a) figures. Although progress is being made in a number of areas, vehicle occupant fatalities have not been falling in line with casualty reduction targets for the year 2010. A sample of 1185 fatal vehicle occupant cases was considered, from ten UK police forces, from the years 1994-2005 inclusive. The main findings were: (1) over 65% of the accidents examined involved driving at excessive speed, a driver in excess of the legal alcohol limit, or the failure to wear a seat belt by a fatality, or some combination of these. (2) Young drivers have the great majority of their accidents by losing control on bends or curves, typically at night in rural areas and/or while driving for ‘leisure’ purposes. These accidents show high levels of speeding, alcohol involvement and recklessness. (3) Older drivers had fewer accidents, but those fatalities they were involved in tended to involve misjudgement and perceptual errors in ‘right of way’ collisions, typically in the daytime on rural rather than urban roads. Blameworthy right of way errors were notably high for drivers aged over 65 years, as a proportion of total fatal accidents in that age group.     

On the prevention of accidents and injuries : A comparative analysis of conceptual frameworks

The meaning of prevention has changed as new applications of the concept have appeared. Ideas presented in eleven different conceptual frameworks are compared. Identification of the frameworks took place through searches in databases and relevant literature. Five are general by nature, while six relate to injuries and accidents. All are supported by just a few parameters, the time dimension being the most prominent. Compatibility was established on three additional dimensions: level (individual, organizational or societal); direction (“bottom-up” or “top-down”); and in relation to the trichotomy “host-agent-environment”. An attempt to synthesize all these dimensions into one general model of accident and injury prevention is presented.     

An extension of the Human Factors Analysis and Classification System for use in open systems

The Human Factors Analysis and Classification System (HFACS), based upon Reason's model of human error in an organisational context, is currently the most widely used human factors accident analysis framework. However, it has been criticised for merely categorising accident data rather than analysing it. Previous research has established statistical associations between the levels and categories within HFACS but has not specified a mechanism by which one category influences subsequent behaviour. This paper extends the approach in two ways. Using the categories of control flaws derived from Leveson's Systems–Theoretical Accident Model and Processes (STAMP) approach, it describes the mechanisms by which categories within HFACS are associated with other categories lower in the organisational hierarchy. It also provides a mechanism by which active failures can promulgate across organisations. The revised methodology HFACS-STAMP is illustrated using the case study of the Uberlingen mid-air collision on 1 July 2002.