A Causal Analysis of Large Vehicle Accidents Through Fault-Tree Analysis

Recent trends indicate that vehicle miles traveled for large trucks is increasing at a higher rate than for other vehicles. The resulting competition between large trucks and other vehicles for highway space can be expected to result in more multivehicle collisions involving large trucks. This paper presents the result of an investigation of the causes and the mechanism related to large vehicle accidents. A fault-tree analysis of large vehicle accidents identifies the individual roles played by driver, vehicle, and environmental factors, as well as their interactions in the accident mechanism. Using accident data for 1984-1986, the probabilities for different basic events in the fault tree were assessed. The most likely events leading to a large vehicle accident, as well as the most effective counter measures, were then identified. The result indicate that the most prevalent form of accidents due to driver-related failures is when a normal driver makes an error in judgment and is unsuccessful in his or her evasive action. For vehicle-related failures, the predominant type of failure is equipment failure, and for environmental-related failures, excessive demand on driver and vehicle performance created by the environmental or roadway factors.     

Coordinability and Consistency in Accident Causation and Prevention: Formal System Theoretic Concepts for Safety in Multilevel Systems

Although a “system approach” to accidents in sociotechnical systems has been frequently advocated, formal system theoretic concepts remain absent in the literature on accident analysis and system safety. To address this gap, we introduce the notions of coordinability and consistency from the hierarchical and multilevel systems theory literature. We then investigate the applicability and the importance of these concepts to accident causation and safety. Using illustrative examples, including the worst disaster in aviation history, and recent incidents in the United States of aircraft clipping each other on the tarmac, we propose that the lack of coordinability is a fundamental failure mechanism causing or contributing to accidents in multilevel systems. We make a similar case for the lack of consistency. Coordinability and consistency become ingredients for accident prevention, and their absence fundamental failure mechanisms that can lead to system accidents. Finally, using the concepts introduced in this work, we identify several venues for further research, including the development of a theory of coordination in multilevel systems, the investigation of potential synergies between coordinability, consistency, and the high reliability organizations paradigm, and the possibility of reframing the view that “sloppy management is the root cause of many industrial accidents” as one of lack of coordinability and/or consistency between management and operations. By introducing and expanding on the concepts of coordinability and consistency, we hope to contribute to the thinking about, and the to language of, accident causation, and prevention and to add to the intellectual toolkit of safety professionals and academics.     

Lessons learned from Toulouse and Buncefield disasters: from risk analysis failures to the identification of atypical scenarios through a better knowledge management

The recent occurrence of severe major accidents has brought to light flaws and limitations of hazard identification (HAZID) processes performed for safety reports, as in the accidents at Toulouse (France) and Buncefield (UK), where the accident scenarios that occurred were not captured by HAZID techniques. This study focuses on this type of atypical accident scenario deviating from normal expectations. The main purpose is to analyze the examples of atypical accidents mentioned and to attempt to identify them through the application of a well-known methodology such as the bow-tie analysis. To these aims, the concept of atypical event is accurately defined. Early warnings, causes, consequences, and occurrence mechanisms of the specific events are widely studied and general failures of risk assessment, management, and governance isolated. These activities contribute to outline a set of targeted recommendations, addressing transversal common deficiencies and also demonstrating how a better management of knowledge from the study of past events can support future risk assessment processes in the identification of atypical accident scenarios. Thus, a new methodology is not suggested; rather, a specific approach coordinating a more effective use of experience and available information is described, to suggest that lessons to be learned from past accidents can be effectively translated into actions of prevention.     

A Flexible Hierarchical Bayesian Modeling Technique for Risk Analysis of Major Accidents

Safety analysis of rare events with potentially catastrophic consequences is challenged by data scarcity and uncertainty. Traditional causation‐based approaches, such as fault tree and event tree (used to model rare event), suffer from a number of weaknesses. These include the static structure of the event causation, lack of event occurrence data, and need for reliable prior information. In this study, a new hierarchical Bayesian modeling based technique is proposed to overcome these drawbacks. The proposed technique can be used as a flexible technique for risk analysis of major accidents. It enables both forward and backward analysis in quantitative reasoning and the treatment of interdependence among the model parameters. Source‐to‐source variability in data sources is also taken into account through a robust probabilistic safety analysis. The applicability of the proposed technique has been demonstrated through a case study in marine and offshore industry.     

Beyond demand and control: The contribution of organizational risk factors in assessing the psychological well-being of health care employees

Abstract

The job demand–control(–support) model is frequently used as a theoretical framework in studies on determinants of psychological well-being. Consequently, these studies are confined to the impact of job characteristics on worker outcomes. In the present study the relation between work conditions and outcomes (job satisfaction, emotional exhaustion, psychological distress, and somatic complaints) is examined from a broader organizational perspective. This paper reports on an analysis that examines both the unique and the additional contribution of organizational characteristics to well-being indicators, beyond those attributed to job characteristics. A total of 706 care staff from three public residential institutions for people with mental or physical disabilities in the Netherlands took part in this research. To assess organizational risk factors a measurement instrument was developed, the organizational Risk Factors Questionnaire (ORFQ), based on the safety-critical factors of the Tripod accident causation model. Factor analyses and reliability testing resulted in a 52-item scale consisting of six reliable sub-scales: staffing resources, communication, social hindrance, training opportunities, job skills, and material resources. These organizational risk factors explained important parts of the variance in each of the outcome measures, beyond that accounted for by demographic variables and job demand–control–support (JDCS) measures. Communication and training opportunities were of central importance to carers’ job satisfaction. Social hindrance, job skills, and material resources explained a substantial amount of unique variance on the negative outcomes investigated.     

Speaking the Truth in Maritime Risk Assessment

Several major risk studies have been performed in recent years in the maritime transportation domain. These studies have had significant impact on management practices in the industry. The first, the Prince William Sound risk assessment, was reviewed by the National Research Council and found to be promising but incomplete, as the uncertainty in its results was not assessed. The difficulty in assessing this uncertainty is the different techniques that need to be used to model risk in this dynamic and data-scarce application area. In previous articles, we have developed the two pieces of methodology necessary to assess uncertainty in maritime risk assessment, a Bayesian simulation of the occurrence of situations with accident potential and a Bayesian multivariate regression analysis of the relationship between factors describing these situations and expert judgments of accident risk. In this article, we combine the methods to perform a full-scale assessment of risk and uncertainty for two case studies. The first is an assessment of the effects of proposed ferry service expansions in San Francisco Bay. The second is an assessment of risk for the Washington State Ferries, the largest ferry system in the United States.     

The Theory of Risk Homeostasis: Implications for Safety and Health

No strategy for countermeasure design or future directions of research in the areas of human behavior which leads to traffic accidents or lifestyle-related diseases can be rationally developed without an acceptable working theory of human behavior in these domains. For this purpose, an attempt has been made to conceptually integrate the available evidence with respect to the role of human behavior in the causation of road accidents. From this integrative effort it would seem that the accident rate is ultimately dependent on one factor only, the target level of risk in the population concerned which acts as the reference variable in a homeostatic process relating accident rate to human motivation. Various policy tactics for the purpose of modifying this target level of risk have been pointed out and the theory of risk homeostasis has been speculatively extended to the areas of lifestyle-dependent morbidity and mortality.     

Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network

Human factors are widely regarded to be highly contributing factors to maritime accident prevention system failures. The conventional methods for human factor assessment, especially quantitative techniques, such as fault trees and bow-ties, are static and cannot deal with models with uncertainty, which limits their application to human factors risk analysis. To alleviate these drawbacks, in the present study, a new human factor analysis framework called multidimensional analysis model of accident causes (MAMAC) is introduced. MAMAC combines the human factors analysis and classification system and business process management. In addition, intuitionistic fuzzy set theory and Bayesian Network are integrated into MAMAC to form a comprehensive dynamic human factors analysis model characterized by flexibility and uncertainty handling. The proposed model is tested on maritime accident scenarios from a sand carrier accident database in China to investigate the human factors involved, and the top 10 most highly contributing primary events associated with the human factors leading to sand carrier accidents are identified. According to the results of this study, direct human factors, classified as unsafe acts, are not a focus for maritime investigators and scholars. Meanwhile, unsafe preconditions and unsafe supervision are listed as the top two considerations for human factors analysis, especially for supervision failures of shipping companies and ship owners. Moreover, potential safety countermeasures for the most highly contributing human factors are proposed in this article. Finally, an application of the proposed model verifies its advantages in calculating the failure probability of accidents induced by human factors.     

Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees

Risk and uncertainty are integral parts of modern technology, and they must be managed effectively to allow the development of reliable, high-quality products. Because so many facets of technology and society involve risk and uncertainty, it is essential that risk management be handled in a systematic manner. Fault-tree analysis is one of the principal methods used in the analysis of systems'safety. Its detailed and systematic deductive structure makes it a valuable tool for design and diagnostic purposes. Point probability and the minimization of the expected failure probability have, until recently, dominated fault-tree analysis. A methodology that incorporates uncertainty analysis, conditional expected risk, and multiple objectives with fault-tree analysis is presented. A computer software package termed the "Distribution Analyzer and Risk Evaluator (DARE) Using Fault Trees," which translates the new methodology into a working decision-support system, is developed. DARE Using Fault Trees is a flexible computer code that is capable of analyzing the risk of the overall system in terms of the probability density function of failure probability. Emphasis is placed on the uncertainty and risk of extreme events. A comparative study between existing codes for fault-tree analysis and DARE demonstrates the strengths of the methodology. A case study for NASA's solid rocket booster is used to perform the comparative analysis.     

Safety culture: under-specified and overrated?

Is the measurement of 'safety culture' a valid management tool in the effort to reduce accident rate and improve safety performance, or is it a fuzzy academic concept, lacking empirical validation? The answer to this question seems to depend on whom one asks. The UK Health and Safety Commission has encouraged companies to improve their safety performance through the development of a 'positive safety culture'. However, academic discussions in this area suggest that the concept remains vague, lacks empirical validation and is used as an 'umbrella term' for all the social and organizational factors that affect accident rate. This paper reviews the existing literature on safety culture and provides some clarification in terms of definition, empirical evidence and theoretical development. A theoretical framework of the mechanisms by which safety culture affects safety behaviours in organizations is proposed. The implications for practical management issues are discussed and future challenges and areas for further research are identified.     

Major Accidents (Gray Swans) Likelihood Modeling Using Accident Precursors and Approximate Reasoning

Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well‐established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents’ relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor‐based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates.     

A review of FaultrEASE version 1.0

Many systems analysts will be surprised to encounter a program which is billed as a fault-tree development program "perform[ing] logical mathematical operations," but which does not perform Boolean reduction. The rather careful wording quoted in the introduction to this review can, in retrospect, be taken to refer to the fact that gates are quantified using formulas from the calculus of probabilities, and not to claim that Boolean reduction is performed. Since this program does not perform Boolean reduction, its use is limited to essentially graphical applications of the type illustrated in Fig. 1. For this limited application, the program has some features which make it attractive; it is easy to develop and print a passable drawing of a fault tree, and it is easy to do "what-if" analyses (looking at the effects of changing connections or statistics). However, for fault-tree analyses of even moderate complexity, a Boolean processor is necessary (a large fault tree for a real problem in which no events are repeated is arguably a pathological case). Many such algorithms exist on DOS machines, and most of them run within (and are limited to) the usual 640k memory limitation. To be fair, it has to be noted that some commercial algorithms of this type cost far, far more than FaultrEASE (their costs are measured in thousands of dollars rather than hundreds).(ABSTRACT TRUNCATED AT 250 WORDS)     

An Illustration of Matrix Formulation for a Probabilistic Risk-Assessment Study

A matrix formulation is described and numerically illustrated to calculate the public risk and identify the dominant contributors to it arising from the operation of a nuclear power plant. The matrix methodology is used as a superstructure in a probabilistic risk-assessment study to organize the calculated probabilities and to facilitate the analysis and documentation effort. The matrix structure is built to manipulate the large amount of data arising from event and fault-tree analysis and other supporting analyses. It lends itself easily to computerization and provides an analytic capability to identify dominant contributors to risk. It is a useful tool for aiding sensitivity analyses and also a potential formalism for standardization of risk-assessment studies. This tool is already used in the two recent comprehensive nuclear power plant risk-assessment efforts, the Zion and Indian Point Safety Studies.     

Safety culture: under-specified and overrated?

Is the measurement of ‘safety culture’ a valid management tool in the effort to reduce accident rate and improve safety performance, or is it a fuzzy academic concept, lacking empirical validation? The answer to this question seems to depend on whom one asks. The UK Health and Safety Commission has encouraged companies to improve their safety performance through the development of a ‘positive safety culture’. However, academic discussions in this area suggest that the concept remains vague, lacks empirical validation and is used as an ‘umbrella term’ for all the social and organizational factors that affect accident rate. This paper reviews the existing literature on safety culture and provides some clarification in terms of definition, empirical evidence and theoretical development. A theoretical framework of the mechanisms by which safety culture affects safety behaviours in organizations is proposed. The implications for practical management issues are discussed and future challenges and areas for further research are identified.     

Understanding Organizational Safety Using Value-Focused Thinking

Decision analysis is recognized as the right way to make risk management decisions, using probabilistic techniques to assess the accident risk. It is also accepted that the decisions that individuals in the organization make affect the likelihood of an accident and thus managerial and organizational factors should be included in the risk modeling process. However, decision analytic techniques have not been used to understand the decisions that are made by these individuals. The initial domain for this research is marine transportation. We use the framework of value-focused thinking in order to understand safety decisions made within our research partner organization, a major domestic oil tanker operator. We describe the results of interviews held with managers and employees from this organization. Through these interviews, we sought to understand the values these experts apply in their roles within the organization and the objectives they seek to achieve to contribute to its overall safety performance. The end result is a framework that not only portrays the fundamental objectives of safe operations for various roles in the organization, but also interconnects these different decision contexts. We believe that this approach is fundamentally different from those used in previous work and that this is an interesting application of value-focused thinking.     

Risk Decision Making in Operational Safety Management– Experience from the Nordic Benchmark Study

Technical Research Centre of Finland (VTT) and Studsvik AB, Sweden, have simulated decision making of the Swedish Nuclear Power Inspectorate and a power company by applying decision models in a benchmark study. Based on the experience from the benchmark study, a decision analysis framework to be used in safety related problems is outlined. By this framework both the power companies and the safety authorities could be provided with a more rigorous, systematic approach in their decision making. A decision analytic approach provides a structure for identifying the information requirements of the problem solving. Thus it could serve as a discussion forum between the authorities and the utilities. In this context, probabilistic safety assessment (PSA) has a crucial role of expressing the plant safety status in terms of reactor core damage accident probability and of risk contributions from various accident precursors. However, a decision under uncertainty should not be based solely on probabilities, particularly when the event in question is a rare one and its probability of occurrence is estimated by means of different kinds of approximations.     

Cost-Benefit Analysis of All-Terrain Vehicles at the CPSC1

The present value of the costs of injuries and deaths associated with each unit of a product is a useful number in conducting cost-benefit analysis at the CPSC. Before a remedy is known, this value indicates the approximate amount that it is worth spending on a fix; similarly, if a fix is proposed, this number indicates whether it is cost-justified. The method of analysis is applied to all-terrain vehicles. Injury costs per vehicle are estimated. Determinants of accidents are estimated using a logit regression model applied to surveys of users and of accident victims; this indicates factors associated with accidents, and is used to estimate marginal probabilities. Costs of various vehicle components are estimated using a hedonic price index. This information (injury costs, accident probabilities, and component cost) is combined in a benefit–cost analysis of proposed remedies.     

Psychosocial variables related to transit safety: The application of catastrophe theory

This research applied a paradigm for the study of occupational safety and health risks in manufacturing settings to the risks associated with urban and regional transit operation. Subjects were 290 transit operators who completed a questionnaire measuring safety management, danger ratings, beliefs about accident control, work experience, physical stress, social stress, anxiety, environmental hazards, transit hazards (assaults and insults upon the operator, the need to reprimand passengers for various infractions, etc.), vehicle crashes and operator injuries, and alcohol and drug use. Principal findings were that operator injuries were most closely associated with transit hazards, which were more frequent at night and on the least desirable routes. Injuries occurred in a climate of elevated stress and anxiety which may have hampered the operators' ability to respond effectively to potentially dangerous situations. The cusp catastrophe model provided a non-linear dynamic explanation for accident occurrence and was more accurate (R = 0.71) for modelling accident incidence than the next best linear alternative (R = 0.51).     

Modeling Ship Transportation Risk

This article presents results from the Commission of the European Communities (CEC) project 'Safety of Shipping in Coastal Waters' (SAFECO). The project was performed by ten European partners during the period 1995-1998. The principal aim of the SAFECO project was to determine the influences that could increase the safety of shipping in coastal waters by analyzing the underlying factors contributing to the marine accident risk level. The work reported here focuses on the Marine Accident Risk Calculation System (MARCS) that was further developed during the SAFECO project. This paper presents the methods used by MARCS, as well as data and results from a 'demonstration of concept' case study covering the North Sea area. The estimated accident frequencies (number of accidents per year) were compared with historical accident data, to demonstrate the validity of the modeling approach. Reasonable (within a factor of 5) to good (within a factor of 2) agreement between calculated accident frequencies and observed accident statistics was generally obtained. However, significant discrepancies were identified for some ship types and accident categories. The risk model has particular problems with estimating the accident frequency for drift grounding in general and powered grounding for ferries. It was concluded that these discrepancies are related to uncertainties in several areas, specifically in the risk model algorithms, the traffic data, the error and failure probability data, and the historical accident statistics.     

The Accident Evolution and Barrier Function (AEB) Model Applied to Incident Analysis in the Processing Industries

This study develops a theoretical model for accident evolutions and how they can be arrested. The model describes the interaction between technical and human-organizational systems which may lead to an accident. The analytic tool provided by the model gives equal weight to both these types of systems and necessitates simultaneous and interactive accident analysis by engineers and human factors specialists. It can be used in predictive safety analyses as well as in post hoc incident analyses. To illustrate this, the AEB model is applied to an incident reported by the nuclear industry in Sweden. In general, application of the model will indicate where and how safety can be improved, and it also raises questions about issues such as the cost, feasibility, and effectiveness of different ways of increasing safety.