The hybrid systems method integrating STAMP and HFACS for the causal analysis of the road traffic accident

A System-Theoretic Accident Model and Process with Human Factors Analysis and Classification System taxonomy

Application of systems thinking accident analysis methods: A review for railways

What do applications of systems thinking accident analysis methods tell us about accident causation? A systematic review of applications between 1990 and 2018

Objective: The goals of this research are to: (i) investigate the contributing factors of major road traffic accidents using a human factors classification that follows the ideas of the human factors analysis and classification system (HFACS); (ii) quantitatively examine the relationships between the human factors of the cross levels in an entire system.Methods: This study examined 234 major road traffic accidents recorded in 27 Chinese provinces from 1997 to 2014. Odds ratio (OR) was used to quantitatively analyze the relationships among the contributing factors.Results: The frequencies of unsafe acts, violations, and inadequate regulation are the highest in five categories, 15 subcategories, and 63 indicators, respectively. This study has demonstrated a number of associations between the upper and adjacent lower levels. At the outside factors level, “failure to provide supervision for regulatory” can be viewed as a strong predictor to “formal accountability for actions,” “norms and rules,” and “values and beliefs.” At the organizational influences level, “formal accountability for actions,” “norms and rules,” and “values and beliefs” were strong predictors. At the unsafe supervision level, “failure to provide oversight,” “failure to initiate corrective action,” and “failure to enforce rules and regulations” had strong prediction on “fatigue driving.” At the preconditions for unsafe acts level, “visual limitation”, “fatigue driving,” and “vehicle faults” were strong predictors.Conclusions: The generic HFACS failure types were interpreted and applied successfully to the road safety context, and such examination of major accidents has provided significant findings concerning the main contributing factors of those accidents. Using the OR technique, this study has demonstrated a number of associations between the upper level and adjacent lower levels in the entire system and has found the routes to failure, which is particularly important for developing countermeasures and remediation strategies, as it ensures that these countermeasures are targeted to a wider range of systems. Furthermore, these findings demonstrate the efficiency and applicability of the HFACS as a retrospective tool for the analysis of major road traffic accidents.

A Delphi study of human factors methods for the evaluation of adaptation in safety-related organisations

A new accident causation theory based on systems thinking and its systemic accident analysis method of work systems

Systems theoretic accident model and process (STAMP): A literature review

New systems-based method to conduct analysis of road traffic accidents

Revising HFACS for SMEs in the chemical industry: HFACS-CSMEs

Accidents in the construction industry remain a significant concern, demanding a comprehensive and systematic approach to their analysis and prevention. This study proposes an innovative method to improve the process of accident analysis in construction by using the Human Factor Analysis and Classification System (HFACS) framework. HFACS, originally developed in aviation, has proven effective in identifying and categorizing human errors contributing to accidents. This research adapts HFACS to the construction context, aiming to provide a complete understanding of the human factors influencing accidents on construction sites. The adapted HFACS framework will serve as a structured tool for analyzing these factors, encompassing organizational, supervisor, and individual levels. The findings are expected to contribute valuable insights into the root causes of accidents, allowing for the development of targeted mediations and preventive measures. The significance of this study lies in the potential to enhance safety practices and minimize accidents in the construction industry. By applying the HFACS framework, construction companies and stakeholders can gain a deeper understanding of the underlying causes of accidents and take proactive steps to mitigate risks. By using the HFACS framework, accident analysis in construction can be improved by systematically identifying and categorizing human errors that contribute to accidents. This systematic approach will help in the development of effective strategies to prevent similar accidents from occurring in the future. This literature review aims to explore previous studies that have utilized the HFACS framework in various industries, such as aviation, maritime, and rail, to improve safety and reduce human errors. Key Words: Accident Analysis, HFACS, HFACS Framework, Safety Management, Human Factors.

Comparison of the theoretical elements and application characteristics of STAMP, FRAM, and 24Model: A major hazardous chemical explosion accident

Accident analysis contributes much to improve the safety management of enterprises. The Human Factors Analysis and Classification System (HFACS) is an accident analysis method popularly used overseas. Based on HFACS analysis method, this paper presents a new accident analysis method combining HFACS with Accident Causality Diagram. On the basis of the clear description of basic events' causal relationship in the accident, the new approach applies HFACS to evaluate the basic events leading to accident, which overcomes the deficiency of HFACS that the ultimate analysis result is not clear enough to understand due to the lack of the association between basic events and the events at other levels in the accident. The new method is used to analyze the collision accident of two vehicles in mining area. It can be concluded that HFACS based on Accident Causality Diagram is feasible and it helps to find out the main reasons that lead to accident and thus to take proper measures to prevent the occurrence of similar accidents.

Created from the original work of James Reason’s Swiss Cheese accident causation model featuring human error and latent organizational influences, the Human Factors Analysis and Classification System (HFACS) has become a proven model for analysing human error in aviation accidents. HFACS classifies human error into four levels of organizational influence that can set the stage for unsafe acts to occur. In modern terms of Safety Management Systems (SMS) proactivity, however, the HFACS is still utilized largely as a reactive accident investigation tool, focused on analysis of historical events to form ideas about system deficiencies and negative trends. This study emphasizes that human error on the bottom portion of the HFACS model often carries a substantial monetary and human cost to the organization, even when an aircraft is not involved in a classified accident. Here, the researchers sought a more proactive and systematic way of pre-identifying latent negative organizational influences causing the costliest human errors and finding mitigating solutions by tapping into front line perspectives. This project began with the development of a strategic aviation leadership course for a commercial aviation organization, “Airline X,” with the intent of gathering qualitative data to systematically address HFACS organizational influences that could lead to costly human error accidents and incidents. Researchers proposed top-down, proactive mitigations based on an extensive thematic analysis of front-line perspectives on various safety threats and other organizational deficiencies. After a year of collecting data from over 1,100 individuals during the leadership course through the Airline X pilot group, the qualitative data was compiled and analysed from the responses to two short surveys; one was given early in the course after guided discussions, and the other at the end of the course. The qualitative methodology enabled categorization of the pilots’ answers into common themes. Ten sub-themes were established, all related to organizational influences, then prioritized, and superimposed on the HFACS. During the study, sub-themes related to ramp safety literally manifested themselves in the form of two costly ramp incidents that resulted in revenue loss, as both aircraft were temporarily removed from service for repair. In a display of prescient, timely feedback from the pilot group and supporting accident data showing the direct cost of a potentially failed ramp policy (organizational influences) as evidence, the researchers recommended a continuous cycle of ‘Bottom up (reactive), Top down (proactive)’ Human Factors Safety Management Systems (HFSMS) feedback to senior and middle management to enhance the company’s existing SMS.

It is axiomatic that 60 to 80 percent of mishaps are attributed to human error. The Human Factors Analysis and Classification System (HFACS) was developed by Dr. Scott Shappell and Dr. Douglas Wiegmann for the U.S. Navy to reduce human error in aircraft operations and maintenance. It is a broad human error framework that was originally used to investigate and analyze human factors aspects of aviation mishaps. HFACS is heavily based upon James Reason's ‘Swiss Cheese’ model of human error mishap causation. The HFACS framework provides a powerful tool to determine incident and accident root causal factors, generate leading indicators for potential mishaps, and target prevention efforts for maximum efficacy of loss prevention through systematic identification of active and latent failures within an organization. Moreover, the HFACS may be used to generate leading as well as lagging indicators for mishap prevention by applying to near-miss investigations. HFACS has seen remarkable success in a variety of complex, tightly-coupled industries subject to large, catastrophic losses due to human error and organizational failure (aerospace, nuclear power generation, mining, construction, rail, and healthcare). The HFACS is adapted and presented for use in offshore operations involving offshore oil and gas exploration, production and support.

Assessment of the Human Factors Analysis and Classification System (HFACS): Intra-rater and inter-rater reliability