Common operations failure modes in the process industries

The Abnormal Situation Management^® (ASM^®) Consortium (This research study was sponsored by the Abnormal Situation Management (ASM) Consortium. ASM^® and Abnormal Situation Management^® are registered trademarks of Honeywell International, Inc.) funded a study to investigate common failure modes and root causes associated with operations practices. The study team analyzed 20 public and 12 private incident reports using the TapRoot^® methodology to identify root causes. These root causes were mapped to operations practice failures. This paper describes the top ten operations failure modes identified in the analysis. Specific recommendations include how to analyze plant incident reports to better understand the sources of systemic failures and improve plant operating practices.     

Application of fire suppression materials on suppression of LNG pool fires

An LNG pool fire is considered one of the main hazards of LNG, together with LNG vapor dispersion. Suppression methods are designed to reduce the hazard exclusion zones, distance to reach radiant heat of 5 kW/m², when an LNG pool fire is considered. For LNG vapor dispersion, the hazard exclusion zone is the distance travelled by the LNG vapor to reach a concentration of 2.5% v/v (half of the LNG lower flammability limit).Warming the LNG vapor to reach positive buoyancy faster is one way to suppress LNG vapor dispersion and reduce evaporation rate (thus fire size and its associated radiant heat) and that is the main objective in LNG pool fire suppression. Based on previous research, the use of high expansion foam has been regarded as the primary method in suppressing LNG pool fires. However, in 1980, another method was introduced as an alternative pool fire suppression system, Foamglas^®. The research concluded that 90% of the radiant heat was successfully reduced. Currently-called Foamglas^® pool fire suppression (Foamglas^® PFS) is a passive mitigation system and is deployed after the leak occurs. Foamglas^® PFS is non-flammable, and has a density one-third of the density of LNG, thus floats when an LNG pool is formed.This paper describes the study and confirmation of Foamglas^®PFS effectiveness in suppressing LNG pool fires. In addition, while Foamglas^® PFS is not expected to suppress LNG vapor dispersion, further investigation was conducted to study the effect of Foamglas^®PFS on LNG vapor dispersion. An LNG field experiment was conducted at Brayton Fire Field. The experimental development, procedures, results and findings are detailed in this paper.     

A risk-based modelling approach to enhance shipping accident investigation

This paper developed a risk-based modelling approach to enhance the execution process of shipping accident investigation (SAI). Specifically, the paper addressed a fuzzy extended fault tree analysis (FFTA) that combines the effects of organizational faults and shipboard technical system failures under a unique risk assessment scheme. The case study illustrates that a novel idea behind the proposed methodology allows relevant accident investigators to clarify the probability of technical failures, operational misapplications, and legislative shortages leading to the shipping accident. The current SAI reports can be extended with an integrated risk assessment section to formulate integrated strategies along with risk control measures onboard ships. Since the consequences of shipping accidents are still a global concern, the paper addresses integration of a FFTA into SAI reports to ensure a consistent database and subsequent decision aid to accident analysis and prevention efforts in the maritime transportation industry.     

A systems perspective of managing error recovery and tactical re-planning of operating teams in safety critical domains

Introduction

Research in human error has provided useful tools for designing procedures, training, and intelligent interfaces that trap errors at an early stage. However, this “error prevention” policy may not be entirely successful because human errors will inevitably occur. This requires that the error management process (e.g., detection, diagnosis and correction) must also be supported. Research has focused almost exclusively on error detection; little is known about error recovery, especially in the context of safety critical systems. The aim of this paper is to develop a research framework that integrates error recovery strategies employed by experienced practitioners in handling their own errors.

Method and Results

A control theoretic model of human performance was used to integrate error recovery strategies assembled from reviews of the literature, analyses of near misses from aviation and command & control domains, and observations of abnormal situations training at air traffic control facilities. The method of system dynamics has been used to analyze and compare error recovery strategies in terms of patterns of interaction, system affordances, and types of recovery plans. System dynamics offer a promising basis for studying the nature of error recovery management in the context of team interactions and system characteristics.

Impact on industry

The proposed taxonomy of error recovery strategies can help human factors and safety experts to develop resilient system designs and training solutions for managing human errors in unforeseen situations; it may also help incident investigators to explore why people's actions and assessments were not corrected at the time.     

A multilevel analysis of procedural justice context

Using a multilevel framework, we hypothesized that both employee perceptions of procedural justice and a work unit level measure of procedural justice context would be associated with employee reports of job satisfaction and organizational commitment. Three hundred and twenty-three employees from 53 branches of a financial services organization were used to test this hypothesis. Hierarchical linear modeling analyses revealed that procedural justice context explained variance in employee job satisfaction beyond that accounted for by individual perceptions of procedural justice. With regard to organizational commitment, this hypothesis was not supported. The results are discussed in connection with contextual aspects of procedural justice. © 1998 John Wiley & Sons, Ltd.     

Passenger behavior in trains during emergency situations

IntroductionThis research presents a methodology for analyzing the behavior of people (passengers and crew) involved in emergency situations on passenger trains.MethodsThis methodological tool centers around a qualitative character study coming from Focus Groups (FG) and in-depth interviews to extract the determinant variables on passenger and crew behavior when faced with certain emergency situations on trains.ResultsThis research has led to the creation of a classification of possible behaviors associated to each type of incident and dependent on certain variables. The qualitative study was used as the basis for modeling stated preference data using logit type discrete choice models to characterize and quantify the behavior. The most important results show that the determinant variables on passenger behavior correspond to the type of emergency suffered (its degree of seriousness), the type of passenger, the reasons for the journey (demands of time), the information received during the incident, the relationship between crew and passengers, the duration of the incident and the conditions (temperature control, availability of water, occupancy of the train), the distance to the destination station, and finally, the outside weather conditions. This research was carried out using the Spanish railway network as its reference, although it is applicable to any geographical area.Impact on IndustryThe results show that the information variable should be considered in the development of future research and that the evidences of this research can be used to develop behavioral models for modeling railway passenger evacuations.     

Duty hours and incidents in flight among commercial airline pilots

Introduction. Working long duty hours has often been associated with increased risk of incidents and accidents in transport industries. Despite this, information regarding the intermediate relationship between duty hours and incident risk is limited. This study aimed to test a work hours/incident model to identify the interplay of factors contributing to incidents within the aviation industry. Methods. Nine hundred and fifty-four European-registered commercial airline pilots completed a 30-item survey investigating self-report attitudes and experiences of fatigue. Path analysis was used to test the proposed model. Results. The fit indices indicated this to be a good fit model (χ²?=?11.066, df?=?5, p?=?0.05; Comparative Fit Index?=?0.991; Normed Fit Index?=?0.984; Tucker–Lewis Index?=?0.962; Root Mean Square of Approximation?=?0.036). Highly significant relationships were identified between duty hours and sleep disturbance (r?=?0.18, p?r?=?0.40, p?r?=?0.43, p?Discussion. A critical pathway from duty hours through to self-reported incidents in flight was identified. Further investigation employing both objective and subjective measures of sleep and fatigue is needed.     

Near crash characteristics among risky drivers using the SHRP2 naturalistic driving study

Problem: Previous research have focused extensively on crashes, however near crashes provide additional data on driver errors leading to critical events as well as evasive maneuvers employed to avoid crashes. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive data on real world driving and offers a reliable methodology to study near crashes. The current study utilized the SHRP2 database to compare the rate and characteristics associated with near crashes among risky drivers. Methods: A subset from the SHRP2 database consisting of 4,818 near crashes for teen (16–19 yrs), young adult (20–24 yrs), adult (35–54 yrs), and older (70+ yrs) drivers was used. Near crashes were classified into seven incident types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups. For rear-end near crashes, near crash severity, max deceleration, and time-to-collision at braking were compared across age. Results: Near crash rates significantly decreased with increasing age (p < 0.05). Young drivers exhibited greater rear-end (p < 0.05) and road departure (p < 0.05) near crashes compared to adult and older drivers. Intersection near crashes were the most common incident type among older drivers. Evasive maneuver type did not significantly vary across age groups. Near crashes exhibited a longer time-to-collision at braking (p < 0.01) compared to crashes. Summary: These data demonstrate increased total near crash rates among young drivers relative to adult and older drivers. Prevalence of specific near crash types also differed across age groups. Timely execution of evasive maneuvers was a distinguishing factor between crashes or near crashes. Practical Applications: These data can be used to develop more targeted driver training programs and help OEMs optimize ADAS to address the most common errors exhibited by risky drivers.     

Modeling the effects of production pressure on safety performance in construction projects using system dynamics

Introduction: Construction incidents occur due to system failures, not due to a single factor such as unsafe behavior or condition. Therefore, construction safety should be investigated using a systematic view capable of illustrating the complex nature of incidents. Construction projects are also often behind their planned schedule and suffer from various pressures caused by contractual deadlines or clients. Previous studies demonstrated that such pressures negatively affect safety performance; however, the process of how production pressure influences safety performance is not fully investigated. Method: The present research aimed to understand the feedback mechanism of how production pressure interactively affects safety performance and safety-related managerial components in a construction project. Ground theory method (GTM) is used to create a conceptual causal loop diagram that shows the relationship between incident rate and other variables such as labor hour, actual and planned progress, safety climate, rework, and safety training. Moreover, a power plant construction project was used as a case study to practically investigate the conceptual model; a case study is employed to build a System Dynamics (SD) model. The simulation model was then validated using behavior reproduction and sensitivity analysis. Results: The results of the inequality statistics show that the simulation model can be used to forecast trends in the incident rate.     

What can the trove of CSB incident investigations teach us? A detailed analysis of information characteristics among chemical process incidents investigated by the CSB

Understanding the commonalities among previous chemical process incidents can help mitigate recurring incidents in the chemical process industry and will be useful background knowledge for designers intending to foster inherent safety. The U.S. Chemical Safety and Hazard Investigation Board (CSB) reports provide detailed and vital incident information that can be used to identify possible commonalities. This study aims to develop a systematic approach for extracting data from the CSB reports with the objective of establishing these commonalities. Data were extracted based on three categories: attributed incident causes, scenarios, and consequences. Seventeen causal factors were classified as chemical indicators or process indicators. Twelve chemical indicators are associated with the hazards of the chemicals involved in the incidents, whereas five process indicators account for the hazards presented by process conditions at the time of the incident. Seven scenario factors represent incident sequences, equipment types, operating modes, process units, domino effects, detonation likelihood for explosion incidents, and population densities. Finally, three consequence factors were selected based on types of chemical incidents, casualties, population densities, and economic losses. Data from 87 CSB reports covering 94 incidents were extracted and analyzed according to the proposed approach. Based on these findings, the study proposes guidelines for future collection of information to provide valuable resources for prediction and risk reduction of future incidents.     

Dynamic failure assessment of an ammonia storage unit: A case study

Chemical Process Industries usually contain a diverse inventory of hazardous chemicals and complex systems required to perform process operations such as storage, separation, reaction, compression etc. The complex interactions between the equipment make them vulnerable to catastrophic accidents. Risk and failure assessment provide engineers with an intuitive tool for decision making in the operation of such plants. Abnormal events and near-miss situations occur regularly during the operation of a system. Accident Sequence Precursors (ASP) can be used to demonstrate the real-time operating condition of a plant. Dynamic Failure Assessment (DFA) methodology is based on Bayesian statistical methods incorporates ASP data to revise the generic failure probabilities of the systems during its operational lifetime.In this paper, DFA methodology is applied on an ammonia storage unit in a specialized chemical industry. Ammonia is stored in cold storage tanks as liquefied gas at atmospheric pressure. These tanks are susceptible to failures due to various abnormal conditions arising due process failures.Tank failures due to three such abnormal conditions are considered. Variation of the failure probability of the safety systems is demonstrated. The authors use ASP data collected from plant specific sources and safety expert judgement. The failure probabilities of some safety systems concerned show considerable deviation from the generic values. The method helps to locate the components which have undergone more degradation over the period and hence must be paid attention to. In addition, a Bayesian predictive model has been used to predict the number of abnormal events in the next time interval. The user-friendly and intuitive nature of the tool makes it appropriate for application in safety assessment reports in process industries.     

Do industrial incidents in the chemical sector create equity market contagion?

IntroductionThis paper examines a number of US chemical industry incidents and their effect on equity prices of the incident company. Furthermore, this paper then examines the contagion effect of this incident on direct competitors.MethodEvent study methodology is used to assess the impact of chemical incidents on both incident and competitor companies.ResultsThis paper finds that the incident company experiences deeper negative abnormal returns as the number of injuries and fatalities as a result of the incident increases. The equity value of the competitor companies suffer substantial losses stemming from contagion effects when disasters that occur cause ten or more injuries and fatalities, but benefit from the incident through increasing equity value when the level of injury and fatality is minor.ConclusionsPresence of contagion suggests collective action may reduce value destruction brought about by safety incidents that result in significant injury or loss of life.Practical ApplicationsThis research can be used as a resource to promote and justify the cost of safety mechanisms within the chemical industry, as incidents have been shown to negatively affect the equity value of the not just the incident company, but also their direct competitors.     

Robustness of the western United States power grid under edge attack strategies due to cascading failures

Power systems are the basic support of modern infrastructures and protecting them from random failures or intentional attacks is an active topic of research in safety science. This paper is motivated by the following two related problems about cascading failures on power grids: efficient edge attack strategies and lower cost protections on edges. Applying the recent cascading model by adopting a local load redistribution rule, where the initial load of an edge ij is (k_ik_j)^θ with k_i and k_j being the degrees of the nodes connected by the edge, we investigate the performance of the power grid of the western United States subject to three intentional attacks. Simulation results show that the effects of different attacks for the network robustness against cascading failures have close relations with the tunable parameter θ. Particularly, the attack on the edges with the lower load in the case of θ < 1.4 can result in larger cascading failures than the one on the edges with the higher load. In addition, compared with the other two attacks, a new attack, i.e., removing the edges with the smallest proportion between the total capacities of the neighboring edges of and the capacity of the attacked edge, usually are prone to trigger cascading failures over the US power grid. Our findings will be not only helpful to protect the key edges selected effectively to avoid cascading-failure-induced disasters, but also useful in the design of high-robustness and low-cost infrastructure networks.     

Extension of TACOM to the complexity of tasks designed for abnormal situations in nuclear power plants

TACOM (TAsk COMplexity) is a measure for evaluating the complexity of tasks prescribed for emergency situations in nuclear power plants. Five sub-measures constituting TACOM represent five different aspects of the task complexity exhibited in operating procedures for emergency situations. The practicality of TACOM has been verified through a series of empirical studies. However, tasks designed for abnormal situations that can significantly affect the safety of nuclear power plants, also need a proper measure for evaluating their complexity. TACOM provides a process, a systematic cognitive task analysis method and a set of guidelines to support its application. Therefore, although the characteristics of abnormal task situations are not the same as those of emergency situations, TACOM seems to be reasonably applied to abnormal situations or at least to offer meaningful insights for developing a measure for evaluating the complexity of tasks in abnormal situations. Thus this study examined the applicability of TACOM to abnormal situations through case studies. Particular attention was paid to the sufficiency and appropriateness of the three methodological tools, which are the process, the cognitive task analysis method and the set of guidelines. Collective consideration of the case studies and the characteristics of tasks prescribed for abnormal situations led us to draw the conclusion that TACOM could be reliably used for abnormal situations as well. This paper reports the process of how to apply TACOM to the tasks of abnormal situations and discusses some lessons learned through this application.     

Individual risk analysis of high-pressure natural gas pipelines

Transmission pipelines carrying natural gas are not typically within secure industrial sites, but are routed across land out of the ownership of the pipeline company. If the natural gas is accidentally released and ignited, the hazard distance associated with these pipelines to people and property is known to range from under 20 m for a smaller pipeline at lower pressure to up to over 300 m for a larger pipeline at higher pressure. Therefore, pipeline operators and regulators must address the associated public safety issues.This paper focuses on a method to explicitly calculate the individual risk of a transmission pipeline carrying natural gas. The method is based on reasonable accident scenarios for route planning related to the pipeline's proximity to the surrounding buildings. The minimum proximity distances between the pipeline and buildings are based on the rupture of the pipeline, with the distances chosen to correspond to a radiation level of approximately 32 kW/m². In the design criteria for steel pipelines for high-pressure gas transmission (IGE/TD/1), the minimum building proximity distances for rural areas are located between individual risk values of 10⁻⁵ and 10⁻⁶. Therefore, the risk from a natural gas transmission pipeline is low compared with risk at the building separated minimum distance from chemical industries.     

Integration of Recursive Operability Analysis,FMECA and FTA for the Quantitative Risk Assessment in biogas plants: Role of procedural errors and components failures

With more than 350 GWh per year and thousands of installations around the world, biogas is an appealing strategy in the field of energy production and industrial waste optimization. In this sense, it is of paramount importance to address the risk associated with such plants, as an increasing trend of accidents have been recorded in the last 20 years. In this work, a representative biogas production plant was considered, and a risk assessment was carried out through the combination of Recursive Operability Analysis and Failure Mode and Effects Criticality Analysis. The methodology is rigorous and allows for both the identification and the quantification of accidental scenarios due to procedural errors and equipment failures, which miss in the literature for the case of biogas. The analysis allows the automatic generation of the Fault Trees for the identified Top Events, which can be numerically solved. Results show that the most critical accidental scenario in the biogas plant here considered is the formation of an explosive air-biogas mixture, which can occur in both anaerobic digester and condensate trap. The calculated probabilities agree with the results available in literature on similar plants. Pumps and Distributed Control System were found to be the most critical components.     

Consequence analysis of an open fire incident in a pesticide storage plant

This paper deals with the consequence assessment of an open fire incident in a Pesticides Storage Facility. Consequences are mainly caused by the atmospheric dispersion of toxic substances produced during the fire and transported downwind to considerable distance. An integrated methodology, based on Computational fluid Dynamics (CFD) techniques and the dimensionless buoyancy flux number, F/U³L, a parameter that can be associated with the flow characteristics, taking advantage of the dynamic similarity of the flow domain, is presented and used for the simulation of the plume dispersion.Rise to the present study gave a real incident, which happened in northern Greece in the beginning of 2004 and constituted the basis for the development of the accident scenarios eventually studied. Owing to the uncertainty in the estimation of source term strength and specifically of the magnitude of the heat released during the incident together with the variation in wind velocity, a parameterization of these two quantities has been applied. Four typical accident scenarios have been designed and studied.It is concluded that the proposed methodology allows for the calculation of the ground level concentration of any non-reactive substance dispersed in the atmosphere and constitutes a complementary approach in the consequence analysis of accidents in agrochemical (pesticides) plants.     

Fault propagation behavior study and root cause reasoning with dynamic Bayesian network based framework

The Bhopal disaster was a gas leak incident in India, considered the world's worst industrial disaster happened around process facilities. Nowadays the process facilities in petrochemical industries have becoming increasingly large and automatic. There are many risk factors with complex relationships among them. Unfortunately, some operators have poor access to abnormal situation management experience due to the lack of knowledge. However these interdependencies are seldom accounted for in current risk and safety analyses, which also belonged to the main factor causing Bhopal tragedy. Fault propagation behavior of process system is studied in this paper, and a dynamic Bayesian network based framework for root cause reasoning is proposed to deal with abnormal situation. It will help operators to fully understand the relationships among all the risk factors, identify the causes that lead to the abnormal situations, and consider all available safety measures to cope with the situation. Examples from a case study for process facilities are included to illustrate the effectiveness of the proposed approach. It also provides a method to help us do things better in the future and to make sure that another such terrible accident never happens again.