A systems approach to accident causation in mining: an application of the HFACS method

Over a decade of UAV incidents: A human factors analysis of causal factors

This analysis examined systemic causes of Uncrewed Air Vehicle (UAV) accidents identifying operator, environmental, supervisory, and organisational factors through the use of the Human Factors Analysis and Classification System (HFACS). HFACS is a system-based analysis method for investigating the causal factors associated with accidents and incidents and has previously been used to reliably and systematically identify active and latent failures associated with both military and general aviation accidents. Whilst HFACS has previously been applied to UAV accidents, the last known application was conducted in 2014. Using reports retrieved from nine accident investigation organisations' databases, causal factors were coded against unsafe acts, preconditions, and failures at the supervisory, organisational, and environmental levels. Causal factors were assessed on 77 medium or large UAV mishaps/accidents that occurred over a 12-year period up to 2024. 42 mishap reports were deemed to involve a human factor as a causal factor. A large proportion of the mishaps contained factors attributed to Decision Errors at level 1 (Unsafe Acts) which was found to be associated with both the Technological Environment and Adverse Mental State at level 2 (Pre-conditions). Causal factors were identified at each of the other 3 levels (Supervisory, Organisational and External) with a number of emergent associations between causal factors. These data provide support for the identification and development of interventions aimed at improving the safety of organisations and advice of regulators for Uncrewed Air Systems.

A Review of Modifiable Health Care Factors Contributing to Inpatient Suicide: An Analysis of Coroners' Reports Using the Human Factors Analysis and Classification System for Healthcare

BACKGROUND

Inpatient suicides have devastating and long-lasting consequences for patients, families, and health care organizations, posing a major challenge for hospitals. Although many studies have identified patient risk factors for inpatient suicide, the modifiable health care factors are less understood. Failure to understand these modifiable factors weakens organizations' ability to design and implement effective prevention strategies.

METHODS

The Human Factors Analysis and Classification System for Healthcare (HFACS-Healthcare) was used to classify and analyze modifiable health care factors that contributed directly or indirectly to inpatient suicides in Australian hospitals between 2009 and 2018. Comparisons were made between general and psychiatric hospital units to identify context-specific recommendations.

RESULTS

Of the 367 cases, 216 (58.9%) had enough information to analyze the contributing factors, and 214 (58.3%) included unit location information. Multiple modifiable health care factors were identified in the cases as contributing to the patients' suicides. Commonly, cases reported decision errors made by individuals (57.4%), problems with the physical environment (56.0%), and unit-level operational decision-making errors (that is, planned inappropriate operations) (48.6%). An association was found between unit type and problems with coordination, mental state, tasks, physical environment, planned inappropriate operations, and organizational culture (p < 0.05).

CONCLUSION

General prevention initiatives may not be effective in addressing inpatient suicides across specialty units. HFACS-Healthcare enabled a deeper understanding of inpatient suicide and the identification of priority areas that, if addressed, could help reduce the number of preventable suicides in hospitals. Hospital suicide prevention initiatives need to be tailored to specific units and target individual and system vulnerabilities to improve safety and reduce inpatient suicide rates.

Analysis of characteristics and causes of gas explosion accidents: a historical review of coal mine accidents in China

Objectives This study aimed to provide greater insight into the characteristics of severe and extraordinarily severe gas explosion accidents (SESGEAs). Methods. The study analyzed the accident characteristics and causes of SESGEAs. As an example, we conducted a specialized case analysis using the 24Model (fourth edition) on the recent Baoma coal mine gas explosion. Results. SESGEA data are characterized by greater volatility, with significant differences in the geographical distribution, temporal distribution and attributed characteristics of the accidents. From the accident analysis: chaotic ventilation management was the most serious accident cause of SESGEAs; unsafe acts related to ventilation operations accounted for 18.51% of all unsafe acts; coal miners lack professional safety knowledge and have a serious fluke mentality in mining work; enterprises have insufficient enforcement of safety procedure documents, and lack of attention to the allocation of underground human resources and safety training systems; and the importance of safety, the role of the safety department and satisfaction with safety facilities have become the most serious missing items of safety culture. Conclusion. This study can provide important data support and management basis to assist mine operators in developing more targeted accident prevention strategies.

Using HFACS to understand human error in railway dispatcher performance: a study of proactive safety inspection records

This study analyzes 4,095 proactive safety inspection records obtained from a large dispatching centre by utilising the HFACS framework. These proactive safety inspection records offer comprehensive documentation of incidents, capturing major accidents and numerous minor discrepancies and lapses that often go unnoticed in accident reports. The analysis revealed that most incidents were attributed to unsafe actions, primarily skill-based errors and poor decision-making. Additionally, contributing factors such as adverse mental states, personal readiness, and crew resource management were found to play a significant role as preconditions for unsafe acts. Path analyses further established a significant correlation between factors such as unsafe supervision, preconditions for unsafe acts, and the occurrence of unsafe acts. In our discussion, we critically evaluate the strengths and limitations of proactive safety inspection records in safety research. Moreover, we emphasise these findings' potential to enhance safety within the railway industry.

Relationships among causal factors influencing mine accidents using structural equation modelling

Accidents occur due to a series of interactions between deficiencies within the various levels of a sociotechnical system. Quantifying the relationship between upper and lower levels helps develop accident countermeasures focusing on significant organisational latent conditions. This study explores the relationship between the causal factors of accidents within Ghanaian mines using SEM. Data obtained from the analysis of incident reports using HFACS-GMI were quantified to enable its use in the SEM software, as SEM calculations cannot be done using a 0/1 description. The study also tests five hypotheses, including the basic assumption of the HFACS model. The case study results showed that organisational factors significantly influence workplace/individual conditions; upper causal categories do not only influence adjacent immediate lower causal categories, and partial correlations exist between causal categories with a particular level. Based on the SEM model from LISERL, an accident causation path diagram was developed. The diagram reveals that leadership flaws, the technological environment and adverse physiological/mental states were the mediating factors in accident causation within the mines. The operational process has a prominent position in the organisational factors tier and is an essential factor in the entire accident system. Therefore, accident countermeasures should be directed to addressing operational deficiencies.

Fatal fall-from-height accidents: Statistical treatment using the Human Factors Analysis and Classification System - HFACS

INTRODUCTION

The civil construction industry (CCI) is one of the most dangerous sectors for occupational accidents. Studies conducted in several countries show that occupational accidents involving falls from height are the main cause of deaths in recent years.

METHOD

This article analyzed the combinations of causal factors with the highest likelihood of accidents involving falls from height in construction to assist in decision-making. The methodology was divided into four stages: accident collection and sample definition; accident analysis; probability determination; and obtaining the theoretical curve of an accident probability distribution. The methodology was applied to reports of fatal fall-from-height accidents that occurred in the United States between 1997 and 2020.

RESULTS

The results show that among the accidents analyzed, the highest probability of fatality is when a roofer aged between 31 and 44 years performs their activity on a roof between 10:00 and 11:59 am. It is also noted that the three causal factors most present in the accidents were: organizational process (97.7%); poor management of worker resources (96.6%); and organizational climate (95.4%). From the probability distribution curve, 68% of the fatal accidents occurred after reaching between 18 and 34 causal factors present in the HFACS method categories.

Influence of communication determinants on safety commitment in a high-risk workplace: a systematic literature review of four communication dimensions

Health, safety, and environment (HSE) are critical aspects of any industry, particularly in high-risk environments, such as the oil and gas industry. Continuous accident reports indicate the requirement for the effective implementation of safety rules, regulations, and practices. This systematic literature review examines the relationship between safety communication and safety commitment in high-risk workplaces, specifically focusing on the oil and gas industry. The review comprises 1,439 articles from 2004 to 2023, retrieved from the Scopus and Web of Science databases following the PRISMA comprehensive guidelines. This study considers safety communication, communication climate, and communication satisfaction to evaluate their influence on safety commitment under occupational health and safety. This study identifies safety commitment issues and their underlying factors, discussing measures for preventing and reducing accidents and incidents and highlighting preventive measures for future research. It also signifies the variables influencing accident and incident rates. The research underscores the importance of communication dimensions and the need for workers to possess adequate skills, knowledge, and attitudes regarding occupational safety and health procedures. Moreover, the study contributes to the industrial and academic domains by improving organizational safety commitment, promoting a safety culture, and developing effective communication strategies. Furthermore, practitioners may benefit from this comprehensive overview in developing, evaluating, and enhancing occupational safety.

Using text mining and multilevel association rules to process and analyze incident reports in China

Incident investigation reports provide information on defects related to the system safety and indications for improvements. Currently, the analysis of these reports relies heavily on expert' experience. The foreseeable work-load and lack of understanding about the importance of near misses have created a situation where severe accidents are rigorously investigated, and minor incidents are often omitted. Consequently, incident reports have not been fully analyzed to provide sufficient solutions. The aim of this research is to propose a framework that uses text mining and multilevel association rules to efficiently structure Chinese incident reports and identify important incident patterns, providing an analysis of trends, rectification strategies, and guidance for safety management. A case study of a construction company in China was conducted using two years of incident data dated 2018-2019, including accidents and near misses. To identify incident elements, a pattern extraction workflow involving TextRank, and domain pertinence was devised based on the linguistic and writing styles of Chinese reports. A concept hierarchy was applied to determine the taxonomic relationships within the risk factors. Multilevel association rule mining was adopted and proven to deliver more comprehensive pattern indications. Comparative and cross-analysis of patterns in different time periods revealed the severity and temporal features of incidents as well as the effectiveness of preventive and precautionary measures. The results also highlight the importance of learning from near miss events. Decision makers can formulate countermeasures and management policies based on these results to improve safety performance.

Study on the emergency capacity of coal mine enterprises in Longdong Area based on D-FAHP method

Emergency capability assessment is a complex system with multiple factors, variables and levels. Incomplete and uncertain assess information often occurs during assessment. Based on this, a method combining D-number theory and fuzzy analytic Hierarchy process (FAHP) is proposed to study the emergency capacity of coal enterprises in Longdong area. On the basis of analyzing the limitation of D-S evidence theory, the D-number theory was optimized and improved. According to the principles of systematicness, feasibility, scientificity and timeliness, a hierarchical structure model of enterprise emergency capability assessment was constructed from the perspective of pre-incident, mid-incident and post-incident, which consisted of 4 first-level indicators and 18 s-level indicators. The weight and importance of the assessment index of emergency response capability are calculated by organically integrating the D-number preference relation with the hierarchy structure. Combined with the assessment results of experts, a quantitative analysis and evaluation of the emergency response capacity of a coal enterprise was conducted by using FAHP. The comprehensive score of the enterprise's emergency response capability was 80.45, and the level of emergency response capacity was "good". The research results show that the D-FAHP method has high reliability in evaluating the emergency response capability of coal enterprises, avoiding the impact of uncertain and incomplete information on the assessment results. This can not only effectively identify the weak links in emergency management, but also meet the emergency decision-making needs of enterprises in the emergency state, which has important guiding significance to improve the ability and level of enterprise emergency management.

An Impacting Factors Analysis of Unsafe Acts in Coal Mine Gas Explosion Accidents Based on HFACS-ISM-BN

With the development of intelligent coal mine construction, China’s coal production safety has been greatly improved, but coal mine gas explosion accidents still cannot be completely avoided and the unsafe acts of miners are an important cause of the accidents. Therefore, this study firstly collected 100 coal mine gas explosion cases in China, improved the framework of human factors analysis and classification system (HFACS) and used it to identify the causes of miners’ unsafe acts in detail. A hierarchy of the impacting factors is established. Then, combining with the interpretive structural model (ISM), the correlation between the impacting factors among different levels, especially among non-adjacent levels, is qualitatively analyzed through expert judgment. Then, the correlation among the contributing factors was quantitatively tested by chi-square test and odds ratio (OR) analysis. On this basis, a Bayesian network (BN) is constructed for the impacting factors of miners’ unsafe acts. The results show that the probability of coal mine gas explosion accident is 20% and 52%, respectively. Among the leading factors, the government’s insufficient crackdown on illegal activities had the greatest impact on miners’ violations, with a sensitive value of 13.2%. This study can provide reference for evaluating the unsafe acts of miners in coal mine gas explosion accidents by the probabilistic method.

Risk Assessment of Unsafe Acts in Coal Mine Gas Explosion Accidents Based on HFACS-GE and Bayesian Networks

Even in the context of smart mines, unsafe human acts are still an important cause of coal mine gas explosion accidents, but there are few models to analyze unsafe human acts in coal mine gas explosion accidents. This study tries to solve this problem through a risk assessment method of unsafe acts in coal mine gas explosion accidents based on Human Factor Analysis and Classification system (HFACS-GE) and Bayesian networks (BN). After verifying the reliability of HFACS-GE framework, a BN model of risk factors of unsafe acts was established with the Chi-square test and odds ratios analysis. After reasoning analysis, risk paths and key risk factors of unsafe acts were obtained, and preventive measures were granted. Based on the analysis of 100 coal mine gas explosion cases, the maximum probability of five kinds of unsafe acts of employees is 38%. Among the 22 risk factors, the mental state of employees has the greatest influence on the habitual violation of regulations, and the sensitivity value is 12.7%. This study can provide technical assistance for the risk management of unsafe acts in coal mine gas explosions.

A model for establishing resilience safety culture For construction industry

Increasing construction injury and fatality rate implies that conventional safety culture is unable to match the increasing requirement of construction industry safety. One of the promising approaches is establishing resilience safety culture for construction industry. For the aim, a hypothesized model was developed and 420 data for testing model was collected by the present study. Structural Equation Modeling technique was employed to test the hypothesized model by fitting the data into the model. Finally, a model consisting of ten dimensions with thirteen relationships was established by the present study. Fuzzy Analytic Hierarchy Process was employed to make a comparison between the proposed model and the other two prevalent models. It was concluded that the proposed model performs better in complying with real situations and considering sufficiently necessary dimensions and relationships. While it is a bit of hard to be easily and fully understood, which points out the direction of further work.

Study of Occupational Safety Risks in Prefabricated Building Hoisting Construction Based on HFACS-PH and SEM

As the concern for environmental pollution and occupational safety caused by the construction industry is gradually increasing worldwide, the prefabricated building model has become a type of construction promoted by sustainable societies. In China, the management codes of prefabricated buildings are not mature enough and safety accidents occur frequently during the construction process. Therefore, how to analyze and determine the main factors that affect the safety of the construction of prefabricated buildings has become a problem to protect the lives and health of construction workers. In this study, we focused our research on the accident-prone component-hoisting construction phase. First, through the questionnaire and accident data, the traditional human factors analysis and classification system (HFACS) was improved into the HFACS-prefabricated building hoisting (PH) risk model. This study also established a comprehensive safety prevention and control system for the component-hoisting process of prefabricated buildings by combining the factor analysis of using structural equation modeling (SEM). The prevention and control measures to avoid the occurrence of prefabricated building component-hoisting accidents were also proposed from four aspects: external environment, organizational factors, prerequisites for triggering accidents, and unsafe leadership behaviors. The results showed the following: (1) For the external environment, occupational safety and health system standards should be established and safety supervision responsibilities should be implemented. (2) For organizational factors, safety management systems should be improved with more capital investment. (3) For unsafe leadership behaviors, safety education and training should be strengthened to ensure workers' optimal physical and psychological states. (4) For the prerequisite of accidents, it is necessary to create a good hoisting work environment.

Analysis of the Interaction Mechanism of the Risk Factors of Gas Explosions in Chinese Underground Coal Mines

Gas explosion accidents easily cause severe casualties in Chinese underground coal mines. Systematic analysis of accident causation is crucial for the prevention of gas explosions. This study identifies the representative risk factors of gas explosions and determines the interrelationship among these risk factors to highlight weak links and develop countermeasures. A total of 21 representative risk factors of gas explosions were identified through 128 case studies and front-line investigations. On this basis, a five-level hierarchical structure model of gas explosions was established to explore the complex interrelationships among the representative risk factors based on a combination of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methods. Moreover, the Matrix of Cross Impact Multiplications Applied to Classification (MICMAC) method was applied to achieve risk factor classification into four clusters, namely, driving factors, linkage factors, dependent factors and autonomous factors. The results indicated that the interrelationships and emergence properties among the risk factors may cause gas explosions, which should give more attention to the interrelationships among multiple factors and multiple subsystems for coal enterprises. Meanwhile, the complex geological conditions, poor safety supervision, inadequate safety education and training, incomplete execution safety regulations and poor safety technology and input are the long-term focus of risk management for coal enterprises. Finally, 10 countermeasures were proposed to control these representative risk factors and interrelationships. The results are helpful to the development of gas explosion risk management policies and to the preferential allocation of limited resources to resolve these issues.

Human factors application for healthcare teams in low- and medium-income countries (LMIC) to help improve patient safety and performance

Mistakes will always happen whether at work or in our personal lives. We can never completely eliminate error, but learning and disseminating lessons from these mistakes to others is essential. Human factors application for colleagues in healthcare, particularly in low- and medium-income countries (LMIC) can greatly improve patient safety and aid better team working and staff morale. Factors such as hunger, dehydration anger, and tiredness, all reduce personal performance and can raise the risk of personal error. It is vital that we understand and optimize interaction within the healthcare team members. As part of this, ineffective communication, steep hierarchy and loss of situational awareness can lead to compromised patient safety and potentially serious error. In this paper, we provide a brief overview of human factors for healthcare colleagues in LMIC. We highlight ways to reduce the chances of error and improve patient safety by recognizing and applying various human factors to our day to day practices.

European Association of Oral Medicine 2021 Conference - Crispian Scully Lecture: Applying Human Factors to Improve Patient Safety and Performance

BACKGROUND

This paper is a synopsis of the Crispian Scully Lecture, presented by one of the authors (PAB), at the 2021 European Association of Oral Medicine (EAOM) Conference in Lisbon, Portugal. It provides an overview of human factors that affect individuals and teams, highlighting ways to reduce the chances of error and improve patient safety.

DISCUSSION AND CONCLUSION

Error is an inevitable and 'normal' part of being human, and it can never be completely eliminated, though learning from mistakes is essential. Human factor application in health care can greatly improve patient safety and lead to better team working and staff morale. Personal factors including tiredness, hunger, dehydration and stress can all reduce performance and raise the risk of clinical error. It is also important to understand and optimise interaction within the clinical team. Poor communication, steep hierarchy and loss of situational awareness can all potentially compromise patient safety.

How to analyse the injury based on 24Model: a case study of coal mine gas explosion injury

BACKGROUND

Coal mine gas explosion injury has caused mass casualties, which have resulted in widespread concern.

METHODS

In order to prevent gas explosion injury in coal mine, 24Model is proposed to analyse the risk in this paper. 24Model is a human-oriented and organisation-oriented risk analysis method. Based on the 24Model, we propose a general procedure for analysing the causes of injury within the organisation.

RESULTS

A coal mine gas explosion case was analysed using the 24Model and the proposed analysis method, and the evolution of injury and the interaction of various causes was showed, and 6 unsafe conditions, 25 unsafe acts, 13 safety knowledge, 13 safety management systems and 13 safety cultures were obtained.

CONCLUSION

Case analysis results show that by using the 24Model and analysis method the proposed effect can help employees to clearly see the evolution and identify the causes of the injury, to better understand the logical relationship with the causes of the injury, improve the effectiveness of training and effectively prevent similar injury. The case study provides a practical procedure for injury investigation and analysis, and thus, preventive measures can be made according to the various causations at different levels.

A systematic approach to public health - Novel application of the human factors analysis and classification system to public health and COVID-19

In this article, we argue for a novel adaptation of the Human Factors Analysis and Classification System (HFACS) to proactive incidence prevention in the public health and in particular, during and in response to COVID-19. HFACS is a framework of causal categories of human errors typically applied for systematic retrospective incident analysis in high-risk domains. By leveraging this approach proactively, appropriate, and targeted measures can be quickly identified and established to mitigate potential errors at different levels within the public health system (from tertiary and secondary healthcare workers to primary public health officials, regulators, and policymakers).

Implementing a human factors approach to RCA2 : Tools, processes and strategies

Root Cause Analysis and Action (RCA2 ) guidelines offer fundamental improvements to traditional RCA. Yet, these guidelines lack robust methods to support a human factors analysis of patient harm events and development of systems-level interventions. We recently integrated a complement of human factors tools into the RCA2 process to address this gap. These tools include the Human Factors Analysis and Classification System (HFACS), the Human Factors Intervention Matrix (HFIX), and a multiple-criterion decision tool called FACES, for selecting effective HFIX solutions. We describe each of these tools and illustrate how they can be integrated into RCA2 to create a robust human factors RCA process called HFACS-RCA2 . We also present qualitative results from an 18-month implementation study within a large academic health center. Results demonstrate how HFACS-RCA2 can foster a more comprehensive, human factors analysis of serious patient harm events and the identification of broader system interventions. Following HFACS-RCA2 implementation, RCA team members (risk managers and quality improvement advisors) also experienced greater satisfaction in their work, leadership gained more trust in RCA findings and recommendations, and the transparency of the RCA process increased. Effective strategies for overcoming implementation barriers, including changes in roles, responsibilities and workload will also be presented.

Improving the Safety-Performance Nexus: A Study on the Moderating and Mediating Influence of Work Motivation in the Causal Link between Occupational Health and Safety Management (OHSM) Practices and Work Performance in the Oil and Gas Sector

The preventive systems required to ensure workers are protected from occupational accidents and injuries dwell heavily on effective occupational health and safety management (OHSM) systems and practices. In this study, the concepts of the job demand-resource model (JD-R), self-determination theory (SDT), and perceived organizational support for safety (POSS) theory were adopted to develop a holistic conceptual model that seeks to unravel moderating and mediating effects of work motivation on the causal link between OHSM practices and work performance in the oil and gas sector. The study measured OHSM practices from six distinct safety dimensional perspectives and work performance using a two-dimensional distinct construct that assesses different aspects of positive work behaviours. A quantitative research approach through the structural equation modelling analysis technique was applied. A total of 1310 participants were selected across three major organizations that represent downstream, upstream, and middle stream of the Ghanaian oil and gas sector. Respondents were recruited through stratified, purposive, and convenient sampling techniques. The findings from the path estimate through the SEM analysis suggested that OHSM practices positively and significantly influenced both safety performance and task performance of employees. However, OHSM practices indicated a higher positive significant influence on task performance than safety performance. The significant influence of OHSM practices on both task and safety performance was significantly moderated and partially mediated by work motivation, while both task performance and safety performance were significantly determined by work motivation. In this study, the dimensions for assessing work performance extend the performance theories established in previous literature, whereas the integrated multifaceted OHSM practices employed diverge from the traditional individualistic approach by providing insights into more flexible managerial practices that are employee-centred and outcome-oriented. The findings from this study address the need for organizations to appreciate the importance of managing workers’ perception of OHSM practices as a motivational drive that induces work performance.

Task rotation in an underground coal mine: Implications on injury and musculoskeletal discomfort

PURPOSE

To investigate the effect of a task rotation schedule on musculoskeletal injury and the challenges of implementing a task rotation schedule within an underground coal mine.

METHODS

This was a pre-post cross-sectional intervention study with two underground coal mines. Participant-surveys were collected at baseline and 12-months.

RESULTS

There were no significant differences in musculoskeletal discomfort between the two sites in any body region. Tasks were rotated two to three times a shift on average.

CONCLUSIONS

The task rotation schedule did not have a significant impact upon musculoskeletal discomfort although this does not necessarily reflect that the rotation schedule was in-effective in curbing injury, rather highlights the complexity of developing a successful task rotation schedule within an underground coal mine. The task rotation schedule, its implementation and execution need consideration and further investigation to assist in effectively controlling injury and fatigue risk.

On the Influence of Human Factors on Safety of Remotely-Controlled Merchant Vessels

With numerous efforts undertaken by both industry and academia to develop and implement autonomous merchant vessels, their safety remains an utmost priority. One of the modes of their operation which is expected to be used is a remote control. Therein, some, if not all, decisions will be made remotely by human operators and executed locally by a vessel control system. This arrangement incorporates a possibility of a human factor occurrence. To this end, a variety of factors are known in the literature along with a complex network of mutual relationships between them. In order to study their potential influence on the safety of remotely-controlled merchant vessels, an expert study has been conducted using the Human Factors Analysis and Classification System-Maritime Accidents (HFACS–MA) framework. The results indicate that the most relevant for the safety of this prospective system is to ensure that known problems are properly and timely rectified and that remote operators maintain their psycho- and physiological conditions. The experts elicited have also assigned higher significance to the causal factors of active failures than latent failures, thus indicating a general belief that operators’ actions represent the final and the most important barrier against accident occurrence.

Analyzing Collision, Grounding, and Sinking Accidents Occurring in the Black Sea Utilizing HFACS and Bayesian Networks

This study examines and analyzes marine accidents that have occurred over the past 20 years in the Black Sea. Geographic information system, human factor analysis and classification system (HFACS), and Bayesian network models are used to analyze the marine accidents. The most important feature distinguishing this study from other studies is that this is the first study to analyze accidents that have occurred across the whole Black Sea. Another important feature is the application of a new HFACS structure to reveal accident formation patterns. The results of this study indicate that accidents occurred in high concentrations in coastal regions of the Black Sea, especially in the Kerch Strait, Novorossiysk, Kilyos, Constanta, Riva, and Batumi regions. The formation of grounding and sinking accidents has been found to be similar in nature; the use of inland and old vessels has been highlighted as important factors in sinking and grounding incidents. However, the sequence of events leading to collision-contact accidents differs from the sequence of events resulting in grounding and sinking accidents. This study aims to provide information to the maritime industry regarding the occurrence of maritime incidents in the Black Sea, in order to assist with reduction and prevention of the marine accidents.

Why the government should be blamed for road safety

The government plays an important role in road safety. However, the effectiveness of the government in the context of road traffic accidents (RTAs) is rarely measured quantitatively. This study aims to quantitatively examine the effects of government regulation on human and organizational factors. A contributing factors classification framework of RTAs is presented based on the human factors analysis and classification system, one of the most popular systems approaches. A total of 405 major RTAs was collected over a 20-year period (1997-2017) in China and analyzed through the structural equation model. The results lead to two main conclusions: the frequency of inadequate regulation, which has reached 343, is the highest frequency among all contributing factors; government regulation exhibits significant effects on organizational influences, unsafe supervision and unsafe behaviors. These findings provide a new perspective for accident prevention that can be initiated by the government in policy-making and regulatory activities.

Analysis of a catastrophic commercial coach crash based on an improved accident causation model: cause classification and lessons learned

Introduction. This study aimed to perform an in-depth analysis of a catastrophic coach crash that occurred on the Chinese expressway, and thus draw useful lessons to avoid similar mistakes. Methods. Various causes were identified from the investigation report based on a proposed accident causation model, which provides a universal pathway for accident analysis from the individual level to the organizational level. Results. Driver error in an emergency affected by fatigue and speeding led directly to the crash. Accordingly, drivers in coaches should be monitored effectively and their unsafe acts must be corrected in a timely manner to avoid the formation of unsafe habits. Based on individual flaws, weaknesses in the construction of the organizational safety management system and safety culture were further deduced and discussed. Conclusion. The work and rest system, as well as the dynamic monitoring system for drivers, should be perfected strictly according to the regulations. Additionally, external factors regarding deficiencies in the design and management of the expressway and the supervision of the transportation company also had great impact on this crash. In summary, more efforts should be taken regarding root causes at the organizational level, regardless of internal or external factors.

Exploring the Underlying Causes of Chinese Eastern Star, Korean Sewol, and Thai Phoenix Ferry Accidents by Employing the HFACS-MA

Maritime safety is a significant topic in the maritime industry since the numerous dangers at sea could lead to loss of property, environmental pollution, and even casualties. Existing research illustrates that human factors are the primary reasons of maritime accidents. Indeed, numerous maritime accidents can be classified into different types of human factors. In this context, the Human Factors Analysis and Classification System for Maritime Accidents (HFACS-MA) model is introduced in this paper. The HFACS-MA framework consists of five levels, complying with the core concepts of HFACS and the guiding principles of the International Maritime Organization (IMO). Based on the five levels of the framework, this research explores the underlying causes of Chinese Eastern Star, Korean Sewol, and Thai Phoenix accidents, and a comparative analysis is conducted. The analysis demonstrates the utility of applying the HFACS-MA model to the maritime industry, and the results emphasize the importance of the following categories: legislation gaps, organizational process, inadequate supervision, communication (ships and VTS), decision errors, and so on. Consequently, the research enables increased support for HFACS-MA and its application and provides valuable information for safety management and policy development in the maritime industry at different levels.

Investigation and Analysis of a Hazardous Chemical Accident in the Process Industry: Triggers, Roots, and Lessons Learned

This paper performs an in-depth investigation and analysis on a catastrophic hazardous chemical accident involving domino effects in China based on an emerging accident causation model—the 24Model. The triggers and roots of the incident from the individual and organizational levels have been identified and several useful lessons have been summarized to avoid similar mistakes. This accident began with a leak of vinyl chloride caused by the failure of the gas holder’s bell housing and the operators’ mishandling. Leaked vinyl chloride was ignited by a high-temperature device in the process of diffusion and the fire quickly spread to the illegally parked vehicles. Several organizations were involved in this accident, and the chemical company should bear the main responsibility for it, and shall establish and implement an effective safety management system in its organizational structure and staffing, facilities management, hazards identification, emergency disposal, etc., to improve safety performance in a systematic way. Enterprises in the chemical industry park shall enhance the communication to clarify major hazard installations in their domains, and conduct regular safety evaluation for the plant as the external environment changed. Government agencies shall plan the layout of the chemical industry park scientifically and ensure safety starts with the design stage. The case study provides a practical procedure for accident investigation and analysis, and thus, preventive measures can be made according to the various causations at different levels.

Dynamics Simulation of the Risk Coupling Effect between Maritime Pilotage Human Factors under the HFACS Framework

Maritime pilotage is an important guarantee for the safety of water traffic in port. The pilot is affected by the complex port environment, the differences of crew and equipment of different ships, the physical and psychological pressure of the pilot himself, as well as the management factors from the pilot station and maritime safety administration. In order to avoid pilotage accidents (PAs), it is necessary to study the coupling effect of human-organizational factors (HOFs) on PAs. In this paper, from the perspective of HOF risk coupling in pilotage, the problem of HOF risk coupling in maritime pilotage is studied by using the hierarchical classification idea of the human factors analysis and classification system (HFACS) and the method of system dynamics (SD). First of all, HFACS is used to analyse the HOF risk causal elements (RCEs) in pilotage, and 70 RCEs are summed up in four layers; secondly, the SD coupling model of RCEs is constructed; finally, based on a dataset of PAs collected by the Shanghai Harbour Pilot Association, the coupling simulation of RCEs in pilotage is carried out, and the volatility is evaluated. In general, the safety situation of maritime pilotage has been improving in the Shanghai port. However, four RCEs (negligence, habit, pilotage experience, and violations) in unsafe acts and two RCEs (teamwork and personal safety awareness) in precondition for unsafe acts contribute the most to maritime PAs and need to be paid attention to.

Analysis of Fall-Related Imminent Danger Orders in the Metal/Nonmetal Mining Sector

Within the metal/nonmetal mining sector, fall-related incidents account for a large proportion of fatal and non-fatal injuries. However, the events and contributing factors leading up to these incidents have not been fully investigated. To help provide a clearer picture of these factors, an analysis of imminent danger orders issued by the Mine Safety and Health Administration (MSHA) between 2010 and 2017 at both surface and underground metal/nonmetal mine sites revealed that most orders are associated with fall risks. Of these cases, 84% involved the workers not using fall protection, fall protection not being provided, or the improper use of fall protection. Fall risks for workers most frequently occurred when standing on mobile equipment, performing maintenance and repairs on plant equipment, or working near highwalls. In most cases, a single, basic, corrective action (e.g., using fall protection) would have allowed workers to perform the task safely. Overall, these findings suggest that a systematic approach is needed to identify, eliminate, and prevent imminent danger situations. Furthermore, to protect mineworkers from falls from height, frequently performed tasks requiring fall protection should be redesigned to eliminate the reliance on personal fall protection.

Cause Analysis of Unsafe Behaviors in Hazardous Chemical Accidents: Combined with HFACs and Bayesian Network

Hazardous chemical accidents (HCAs) seriously endanger public life, property, and health. Human and organizational factors are important causes of many kinds of accidents. In order to systematically explore the influencing factors of unsafe behaviors in HCAs in China, the method of human factors analysis and classification system based on the Bayesian network (BN-HFACs) was introduced. According to the 39 investigation reports of HCAs in China, the origin Bayesian network (BN) was obtained and the failure sensitivity of every node in BN was calculated. The results have shown that hazardous material environment (1.63) and mechanical equipment (0.49) in the level of preconditions of unsafe behavior have the same direction failure effect with operation error, while there is no factor has the same direction failure effect with operation violate. Some factors in organization influence and unsafe supervision, such as organization climate (0.34), operation guidance (0.37), planned operation (0.22), and legal supervision (0.19), are also important reasons for operational errors, while resource management (0.12), hidden investigation (0.18) and legal supervision (0.13) have an impact on operation violates. Moreover, there are still close relationships between other hierarchical elements, such as the operation guidance effect on the hazardous material environment (6.60), and the organizational climate has the most obvious impact on other factors at the level of organizational factors. Based on the above research conclusions, suggestions for individual, enterprise, and government were put forward, respectively, and the limitations of this study were also clarified.

Human factors related to major road traffic accidents in China

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.

Study on the Relationship between Worker States and Unsafe Behaviours in Coal Mine Accidents Based on a Bayesian Networks Model

Unsafe behaviours, such as violations of rules and procedures, are commonly identified as important causal factors in coal mine accidents. Meanwhile, a recurring conclusion of accident investigations is that worker states, such as mental fatigue, illness, physiological fatigue, etc., are important contributory factors to unsafe behaviour. In this article, we seek to provide a quantitative analysis on the relationship between the worker state and unsafe behaviours in coal mine accidents, based on a case study drawn from Chinese practice. Using Bayesian networks (BN), a graphical structure of the network was designed with the help of three experts from a coal mine safety bureau. In particular, we propose a verbal versus numerical fuzzy probability assessment method to elicit the conditional probability of the Bayesian network. The junction tree algorithm is further employed to accomplish this analysis. According to the BN established by expert knowledge, the results show that when the worker is in a poor state, the most vulnerable unsafe behaviour is violation, followed by decision-making error. Furthermore, insufficient experience may be the most significant contributory factor to unsafe behaviour, and poor fitness for duty may be the principal state that causes unsafe behaviours.

Exploring the Contributory Factors of Confined Space Accidents Using Accident Investigation Reports and Semistructured Interviews

Background

The oil and gas industry is one of the riskiest industries for confined space injuries. This study aimed to understand an overall picture of the causal factors of confined space accidents through analyzing accident reports and the use of a qualitative approach.

Methods

Twenty-one fatal occupational accidents were analyzed according to the Human Factors Analysis and Classification System approach. Furthermore, thirty-three semistructured interviews were conducted with employees in different roles to capture their experiences regarding the contributory factors. The content analyses of the interview transcripts were conducted using MAXQDA software.

Results

Based on accident reports, the largest proportions of causal factors (77%) were attributed to the organizational and supervisory levels, with the predominant influence of the organizational process. We identified 25 contributory factors in confined space accidents that were causal factors outside of the original Human Factors Analysis and Classification System framework. Therefore, modifications were made to deal with factors outside the organization and newly explored causal factors at the organizational level. External Influences as the fifth level considered contributory factors beyond the organization including Laws, Regulations and Standards, Government Policies, Political Influences, and Economic Status categories. Moreover, Contracting/Contract Management and Emergency Management were two extra categories identified at the organizational level.

Conclusions

Preventing confined space accidents requires addressing issues from the organizational to operator level and external influences beyond the organization. The recommended modifications provide a basis for accident investigation and risk analysis, which may be applicable across a broad range of industries and accident types.

Evaluating Targeted Intervention on Coal Miners' Unsafe Behavior

Miners’ unsafe behavior is the main cause of roof accidents in coal mines, and behavior intervention plays a significant role in reducing the occurrence of miners’ unsafe behavior. However, traditional behavior intervention methods lack pertinence. In order to improve the intervention effect and reduce the occurrence of coal mine roof accidents more effectively, this study proposed a targeted intervention method for unsafe behavior. The process of targeted intervention node locating was constructed, and based on the analysis of 331 coal mine roof accidents in China, three kinds of targeted intervention nodes were located. The effectiveness of targeted intervention nodes was evaluated by using structural equation model (SEM) through randomly distributing questionnaires to miners of Pingdingshan coal. The results show that, in preventing roof accidents of coal mines, the targeted intervention nodes have a significant positive impact on the intervention effect. The method can also be applied to the safety management of other industries by adjusting the node location and evaluation process.

Characteristic Analysis of Unsafe Behavior by Coal Miners: Multi-Dimensional Description of the Pan-Scene Data

As a high-risk occupation, coal mining has many accidents, primarily due to the unsafe behavior of coal miners. Based on the research of analysis of unsafe behavior and pan-scenario data of miners, a theoretical framework for the analysis of unsafe behavior characteristics was proposed in this paper. The collected data were divided into realistic scenes and abstract scenes according to different manifestations; the pan-scene data were described from the eight dimensions of time, behavioral trace, location, behavioral property, behavioral individual, degree, unsafe action, and specialty using a quantitative method for the structure conversion; and the rules were discovered through cluster analysis and association analysis. A total of 225 coal mine gas explosion accidents were used for analysis, and the pan-scene data description and structure conversion of unsafe behavior that caused these accidents were realized. In a certain cluster, the distribution rules of dimensions and the interaction between different dimensions of unsafe behavior were explored after analysis. The results show that the proposed eight dimensions can fully explain the basic characteristics and attributes of the unsafe behavior of coal miners. The structure conversion can reduce the workload of managers and effectively improve the safety data processing capabilities, and the result of data analysis can provide data support and a management basis for safety management. A new method and thought for the data analysis of miners' unsafe behavior is provided.

Effects of human and organizational deficiencies on workers' safety behavior at a mining site in Iran

OBJECTIVES

Throughout the world, mines are dangerous workplaces with high accident rates. According to the Statistical Center of Iran, the number of occupational accidents in Iranian mines has increased in recent years. This study investigated and analyzed the human and organizational deficiencies that influenced Iranian mining accidents.

METHODS

In this study, the data associated with 305 mining accidents were analyzed using a systems analysis approach to identify critical deficiencies in organizational influences, unsafe supervision, preconditions for unsafe acts, and workers' unsafe acts. Partial least square structural equation modeling (PLS-SEM) was utilized to model the interactions among these deficiencies.

RESULTS

Organizational deficiencies had a direct positive effect on workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.23). The effect of unsafe supervision on workers' violations and workers' errors was also significant, with path coefficients of 0.14 and 0.20, respectively. Likewise, preconditions for unsafe acts had a significant effect on both workers' violations (path coefficient, 0.16) and workers' errors (path coefficient, 0.21). Moreover, organizational deficiencies had an indirect positive effect on workers' unsafe acts, mediated by unsafe supervision and preconditions for unsafe acts. Among the variables examined in the current study, organizational influences had the strongest impact on workers' unsafe acts.

CONCLUSIONS

Organizational deficiencies were found to be the main cause of accidents in the mining sector, as they affected all other aspects of system safety. In order to prevent occupational accidents, organizational deficiencies should be modified first.

Analysis of human and organizational factors that influence mining accidents based on Bayesian network

Purpose. The present study aimed to analyze human and organizational factors involved in mining accidents and determine the relationships among these factors. Materials and methods. In this study, the human factors analysis and classification system (HFACS) was combined with Bayesian network (BN) in order to analyze contributing factors in mining accidents. The BN was constructed based on the hierarchical structure of HFACS. The required data were collected from a total of 295 cases of Iranian mining accidents and analyzed using HFACS. Afterward, prior probability of contributing factors was computed using the expectation-maximization algorithm. Sensitivity analysis was applied to determine which contributing factor had a higher influence on unsafe acts to select the best intervention strategy. Results. The analyses showed that skill-based errors, routine violations, environmental factors and planned inappropriate operation had higher relative importance in the accidents. Moreover, sensitivity analysis revealed that environmental factors, failed to correct known problem and personnel factors had a higher influence on unsafe acts. Conclusion. The results of the present study could provide guidance to help safety and health management by adopting proper intervention strategies to reduce mining accidents.

Safety leadership and systems thinking: application and evaluation of a Risk Management Framework in the mining industry

Safety leadership is an important factor in supporting safety in high-risk industries. This article contends that applying systems-thinking methods to examine safety leadership can support improved learning from incidents. A case study analysis was undertaken of a large-scale mining landslide incident in which no injuries or fatalities were incurred. A multi-method approach was adopted, in which the Critical Decision Method, Rasmussen's Risk Management Framework and Accimap method were applied to examine the safety leadership decisions and actions which enabled the safe outcome. The approach enabled Rasmussen's predictions regarding safety and performance to be examined in the safety leadership context, with findings demonstrating the distribution of safety leadership across leader and system levels, and the presence of vertical integration as key to supporting the successful safety outcome. In doing so, the findings also demonstrate the usefulness of applying systems-thinking methods to examine and learn from incidents in terms of what 'went right'. The implications, including future research directions, are discussed. Practitioner Summary: This paper presents a case study analysis, in which systems-thinking methods are applied to the examination of safety leadership decisions and actions during a large-scale mining landslide incident. The findings establish safety leadership as a systems phenomenon, and furthermore, demonstrate the usefulness of applying systems-thinking methods to learn from incidents in terms of what 'went right'. Implications, including future research directions, are discussed.

Development of a multilevel health and safety climate survey tool within a mining setting

INTRODUCTION

This study aimed to design, implement and evaluate the reliability and validity of a multifactorial and multilevel health and safety climate survey (HSCS) tool with utility in the Australian mining setting.

METHODS

An 84-item questionnaire was developed and pilot tested on a sample of 302 Australian miners across two open cut sites.

RESULTS

A 67-item, 10 factor solution was obtained via exploratory factor analysis (EFA) representing prioritization and attitudes to health and safety across multiple domains and organizational levels. Each factor demonstrated a high level of internal reliability, and a series of ANOVAs determined a high level of consistency in responses across the workforce, and generally irrespective of age, experience or job category. Participants tended to hold favorable views of occupational health and safety (OH&S) climate at the management, supervisor, workgroup and individual level.

CONCLUSION

The survey tool demonstrated reliability and validity for use within an open cut Australian mining setting and supports a multilevel, industry specific approach to OH&S climate. Findings suggested a need for mining companies to maintain high OH&S standards to minimize risks to employee health and safety. Future research is required to determine the ability of this measure to predict OH&S outcomes and its utility within other mine settings.

PRACTICAL APPLICATIONS

As this tool integrates health and safety, it may have benefits for assessment, monitoring and evaluation in the industry, and improving the understanding of how health and safety climate interact at multiple levels to influence OH&S outcomes.

Mass Casualty Incidents in the Underground Mining Industry: Applying the Haddon Matrix on an Integrative Literature Review

OBJECTIVE

Underground mining is associated with obvious risks that can lead to mass casualty incidents. Information about such incidents was analyzed in an integrated literature review.

METHODS

A literature search (1980-2015) identified 564 modern-era underground mining reports from countries sharing similar occupational health legislation. These reports were condensed to 31 reports after consideration of quality grading and appropriateness to the aim. The Haddon matrix was used for structure, separating human factors from technical and environmental details, and timing.

RESULTS

Most of the reports were descriptive regarding injury-creating technical and environmental factors. The influence of rock characteristics was an important pre-event environmental factor. The organic nature of coal adds risks not shared in hard-rock mines. A sequence of mechanisms is commonly described, often initiated by a human factor in interaction with technology and step-wise escalation to involve environmental circumstances. Socioeconomic factors introduce heterogeneity. In the Haddon matrix, emergency medical services are mainly a post-event environmental issue, which were not well described in the available literature. The US Quecreek Coal Mine incident of 2002 stands out as a well-planned rescue mission.

CONCLUSION

Evaluation of the preparedness to handle underground mining incidents deserves further scientific attention. Preparedness must include the medical aspects of rescue operations. (Disaster Med Public Health Preparedness. 2018;12:138-146).

Fitting methods to paradigms: are ergonomics methods fit for systems thinking?

The issues being tackled within ergonomics problem spaces are shifting. Although existing paradigms appear relevant for modern day systems, it is worth questioning whether our methods are. This paper asks whether the complexities of systems thinking, a currently ubiquitous ergonomics paradigm, are outpacing the capabilities of our methodological toolkit. This is achieved through examining the contemporary ergonomics problem space and the extent to which ergonomics methods can meet the challenges posed. Specifically, five key areas within the ergonomics paradigm of systems thinking are focused on: normal performance as a cause of accidents, accident prediction, system migration, systems concepts and ergonomics in design. The methods available for pursuing each line of inquiry are discussed, along with their ability to respond to key requirements. In doing so, a series of new methodological requirements and capabilities are identified. It is argued that further methodological development is required to provide researchers and practitioners with appropriate tools to explore both contemporary and future problems. Practitioner Summary: Ergonomics methods are the cornerstone of our discipline. This paper examines whether our current methodological toolkit is fit for purpose given the changing nature of ergonomics problems. The findings provide key research and practice requirements for methodological development.

Safety of Workers in Indian Mines: Study, Analysis, and Prediction

Background

The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent.

Methods

The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc.

Results

The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed.

Conclusion

Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

Understanding causes of fall and struck-by incidents: What differentiates construction safety in the Arabian Gulf region?

Rapid growth in the Arabian Gulf region has fueled an explosive pace of construction and a rise in risks of occupational injury. Scarcity of pertinent data, however, makes it hard to determine whether accident characteristics, causal factors and remedial interventions identified elsewhere apply to the Gulf in comparable ways. This difficulty stems from unusual construction sector characteristics, notably a heterogeneous mix of expatriate laborers and firms working without a common language, work culture or labor practices. Does this change the mix of accident types or the ranking of main causes and priority remedies? To answer this question, a sample of 519 incident records was analyzed to determine whether accident types and frequencies are comparable to elsewhere. Site safety experts were then interviewed to determine whether rankings of factors and interventions should be similar. Findings are that types are indeed comparable, but the rankings of factors and interventions may not be. Main factors have to do with worker skills and training, experience, use of safety gear and risk perception. The overarching safety issue, however, is that firms and governments do not have strong incentive to address these factors.