Showing 3 results for Hfacs
G. A. Shirali, E. Karami, Z. Goodarzi,
Volume 3, Issue 3 (12-2013)
Abstract
Introduction: Although risk assessment and accident prevention program have been widely used in industries such as steel industry, there are still numerous accidents in these industries. Hence, applying an accident analysis method can identify the root causes and casual factors of accidents and causal factors. Human Factors Analysis and Classification System can identify human errors in the steel industry by using an analysis of past events. The aim of this study was to identify the human errors in the steel industry using the HFACS methodology.
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Material and Method: In this study first, incident reports of industries with high risk, such as Ahvaz steel and pipe industries existing in the department of work and social security was gathered. Then, an analysis of accident was done based on HFACS model. This model has 4 levels and 18 categories which are 1 - unsafe acts of operators (that includes four subtypes) 2 - pre-conditions for unsafe acts (with seven categories) 3 - unsafe supervision (includes four categories) and 4 - the effect of association (with three categories).
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Result: In this study, 158 reports of accident in Ahvaz steel industry were analyzed by HFACS technique. This analysis showed that most of the human errors were: in the first level was related to the skill-based errors, in the second to the physical environment, in the third level to the inadequate supervision and in the fourth level to the management of resources.
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Conclusion: Studying and analyzing of past events using the HFACS technique can identify the major and root causes of accidents and can be effective on prevent repetitions of such mishaps. Also, it can be used as a basis for developing strategies to prevent future events in steel industries.
Farnaz Asghari, Rasoul Hemmatjou, Abolfazl Ghahramani,
Volume 15, Issue 3 (10-2025)
Abstract
Introduction: Unsafe acts are one of the main causes of workplace accidents. Given the critical role of the steel industry in our country, and the limited research on human factors, and the importance of identifying the contributors to accidents, this study was conducted with the aim of identifying human factors influencing accidents and unsafe behaviors using the Human Factors Analysis and Classification System (HFACS). The identified factors were then prioritized using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) methods. Based on the results, appropriate recommendations were proposed for the prevention of accidents and the reduction of unsafe acts.
Material and Methods: This descriptive-analytical study was carried out in the rebar production unit of a steel manufacturing plant. Among 35 recorded accidents over the past two years, 28 were related to the rebar production unit. Data were collected through review of accident reports, seven on-site observations during high-risk shifts, and interviews with employees. After analyzing the occupational accidents, the rebar production process in the rolling unit was identified as a high-risk area. The HFACS checklist was used to assess this process and classify the human factors contributing to accidents. Subsequently, DEMATEL and ANP methods were applied to determine causal relationships and prioritize the factors.
Results: The HFACS analysis identified 236 human factors, among which the preconditions for unsafe acts and organizational factors had the highest frequency (24.57% each), while external factors had the lowest (8.47%). According to DEMATEL results, organizational influences exerted the greatest impact on other levels, whereas external factors had the least effect. In terms of being influenced by other levels, unsafe acts showed the highest level of susceptibility, whereas unsafe supervision had the lowest levels. Based on ANP findings, the preconditions for unsafe acts had the highest importance, while unsafe supervision had the lowest in contributing to unsafe acts.
Conclusion: The findings of this study suggest that improving safety culture, improving organizational regulations, implementing targeted training programs, and updating equipment can play a significant role in reducing accidents caused by unsafe acts. The results provide practical insights for managers and policymakers and can serve as a useful tool for decision-making in occupational health and safety within the steel industry.
Morteza Pajoohnia, Fakhradin Ghasemi, Shahram Mahmoudi Herris, Leila Omidi,
Volume 16, Issue 1 (3-2026)
Abstract
Introduction: The present study was conducted with the objectives of identifying the human and organizational factors contributing to a drum fall accident, classifying these contributing factors based on the Human Factors Analysis and Classification System (HFACS) framework, and prioritizing safety recommendations using Multi-Criteria Decision-Making (MCDM) techniques.
Material and Methods: The HFACS technique was initially applied across its four levels to determine the human and organizational factors involved in the HP drum fall accident from a rotator within a manufacturing industry. Subsequently, the proposed safety recommendations were prioritized using the Best-Worst Method (BWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), based on four criteria: effectiveness, initial cost, reliability, and maintainability.
Results: The contributing factors identified in this study included inattention to the longitudinal movement of the drum during rotation on the rotator, as well as non-compliance with the rotator’s loading capacity relative to its mechanical strength and associated equipment (HFACS Level 1); failure to conduct a design risk assessment to identify critical points related to structural balance and stability (HFACS Level 2); non-adherence to the manufacturing sequence (HFACS Level 3); and the omission of a mechanical locking system for the rotator on the rail and failure to use certified rotating equipment with specified capacities (HFACS Level 4). The three safety recommendations identified with the highest priority were “using certified rotating equipment with specified capacity limits (relative closeness coefficient = 0.822)”, “adhering to the standard drum fabrication sequence (0.749)”, and “the on-site presence of a supervisor or foreman (0.698)”.
Conclusion: The ultimate objective of safety management systems is to propose corrective safety measures based on findings from accident analysis. Implementing safety recommendations as a structured framework not only prevents accident occurrence but also establishes protective layers that mitigate the recurrence of similar accidents in the future.
