Two discrete choice experiments on laboratory safety decisions and practices

IntroductionThe path toward enhancing laboratory safety requires a thorough understanding of the factors that influence the safety-related decision making of laboratory personnel. Method: We developed and administered a web-based survey to assess safety-related decision making of laboratory personnel of a government research organization. The survey included two brief discrete choice experiments (DCEs) that allowed for quantitative analysis of specific factors that potentially influence safety-related decisions and practices associated with two different hypothetical laboratory safety scenarios. One scenario related to reporting a laboratory spill, and the other scenario involved changing protective gloves between laboratory rooms. The survey also included several brief self-report measures of attitude, perception, and behavior related to safety practices. Results: Risk perception was the most influential factor in safety-related decision making in both scenarios. Potential negative consequences and effort associated with reporting an incident and the likelihood an incident was detected by others also affected reporting likelihood. Wearing gloves was also affected somewhat by perceived exposure risk, but not by other social or work-related factors included in the scenarios. Conclusions: The study demonstrated the promise of DCEs in quantifying the relative impact of several factors on safety-related choices of laboratory workers in two hypothetical but realistic scenarios. Participants were faced with hypothetical choice scenarios with realistic features instead of traditional scaling techniques that ask about attitudes and perceptions. The methods are suitable for addressing many occupational safety concerns in which workers face tradeoffs in their safety-related decisions and behavior. Practical Application: Safety-related decisions regarding laboratory practices such as incident reporting and use of PPE were influenced primarily by workers’ perceptions of risk of exposure and severity of risks to health and safety. This finding suggests the importance of providing laboratory workers with adequate and effective education and training on the hazards and risks associated with their work. DCEs are a promising research method for better understanding the relative influences of various personal, social, and organizational factors that shape laboratory safety decisions and practices. The information gained from DCEs may lead to more targeted training materials and interventions.     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

Project risk identification and assessment simultaneously using multi-attribute group decision making technique

The identification and assessment of project risks among potential risks can be considered a multi-attribute group decision making (MAGDM) problem including both quantitative and qualitative criteria. We extend the concept of safety to risk identification and assessment; this is to emphasize that the focus should not only be on the time and cost criteria, but also on the health, safety and environment (HSE) criterion. Conventional approaches to risk identification and risk assessment separately tend to be less effective in dealing with the imprecise of the risk assessment individually. The aim of this paper is to present a new methodology for identifying and assessing risks simultaneously by applying MAGDM technique. This paper includes a new procedure for classifying potential risks which it is named potential risk breakdown structure (PRBS) based on project work breakdown structure (WBS). Nominal group technique (NGT) is utilized for gathering potential risks. Obtained results have been applied in gas refinery plant construction successfully.     

A quantitative risk management framework for dust and hybrid mixture explosions

Dust and hybrid-mixture explosions continue to occur in industrial processes that handle fine powders and flammable gases. Considerable research is therefore conducted throughout the world with the objective of both preventing the occurrence and mitigating the consequences of such events. In the current work, research has been undertaken to help move the field of dust explosion prevention and mitigation from its current emphasis on hazards (with an accompanying reliance on primarily engineered safety features) to a focus on risk (with an accompanying reliance on hierarchical, risk-based, decision-making tools). Employing the principles of quantitative risk assessment (QRA) of dust and hybrid-mixture explosions, a methodological framework for the management of these risks has been developed.The QRA framework is based on hazard identification via credible accident scenarios for dust explosions, followed by probabilistic fault-tree analysis (using Relex – Reliability Excellence – software) and consequence severity analysis (using DESC – Dust Explosion Simulation Code – software). Identification of risk reduction measures in the framework is accomplished in a hierarchical manner by considering inherent safety measures, passive and active engineered devices, and procedural measures (in that order). An industrial case study is presented to show how inherent safety measures such as dust minimization and dust/process moderation can be helpful in reducing dust and hybrid-mixture explosion consequences in a 400-m³ polyethylene storage silo.     

Quantitative assessment of domino scenarios by a GIS-based software tool

A software procedure was developed for the quantitative assessment of domino effect. The procedure was based on a systematic methodology for the identification of domino scenarios and for the assessment of consequences and expected frequencies of the escalation events. A geographical information system (GIS) platform was interfaced to the domino assessment software. The implementation of plant lay-out data to the GIS allowed the automatic identification of the possible targets of escalation effects by the software procedure, and a straightforward calculation of the contribution to individual and societal risk indexes caused by the possible domino scenarios. The procedure was applied to the analysis of several case-studies based on actual plant lay-outs. The results evidenced that the approach allows the quantitative assessment of risk caused by escalation events with a limited additional effort with respect to that required by a conventional QRA. The use of a GIS-based software was a key element in the limitation of the effort required for the quantitative assessment of domino scenarios. Moreover, the results of the case-studies pointed out that the estimation of risk increase due to domino events is an important tool for an effective assessment and control of industrial risk in chemical and process plants.     

Confidence-based quantitative risk analysis for offshore accidental hydrocarbon release events

Quantitative risk analysis (QRA) has been widely used to conduct the assessment of offshore accidental risks. However, the accuracy and validity of QRA is significantly affected by uncertainties when subjective judgments are involved. Therefore, it is unrealistic to determine the probability of a hazardous event by using one single explicit value when safety experts have a relatively low confidence level in their judgments. This paper proposes a new methodology for incorporating uncertainties into conventional QRA using the concept of confidence level. Offshore hydrocarbon release hazards are focused on and a barrier and operational risk analysis (BORA-Release) method is selected as the basic model to illustrate the proposed methodology. A left–right (L–R) bell-shaped fuzzy number is employed and its membership curve is able to control its shape to represent different confidence levels. As to the complex geometry of the bell-shaped fuzzy number, an α-cut operation is introduced to conduct the arithmetic operations of the fuzzy number, and a defuzzification method with total integral value is chosen to match the α-cut operations and acquire complete information for the fuzzy numbers. In the meantime, an optimism index is used to describe the attitude of the decision-maker. One case study is provided in this paper to demonstrate the implementation of this method.     

Risk perception by offshore workers on UK oil and gas platforms

This paper reports the first investigation of risk perception by workers on offshore oil and gas installations on the UK Continental Shelf, following changes in offshore safety legislation in the wake of the Piper Alpha disaster in 1988. The Offshore Safety Case regulations (Health and Safety Executive, 1992, A Guide to the Offshore Installations (Safety Case) Regulations) put the onus on the operator to identify the major hazards and to reduce the risks to As Low As is Reasonably Practicable (ALARP). The regulations specifically state that Quantitative Risk Assessments (QRA) must be used when preparing the Safety Case. However, people do not use QRA when making everyday judgements about risk; they make subjective judgements known as risk perceptions, which are influenced by a number of different factors. This study was designed to complement the extensive QRA calculations that have already been carried out in the development of Safety Cases. The aim was to measure subjective risk perception in offshore personnel and examine how this relates to the more objective risk data available, namely accident records and QRA calculations. This paper describes the Offshore Risk Perception Questionnaire developed to collect the data and reports on UK offshore workers' perceptions of the risks associated with major and minor hazards, work tasks and other activities aboard production platforms.     

Is risk analysis a useful tool for improving process safety?

To improve safety one has to know where risks are. For determining risks, hazards have to be identified and representative accident scenarios defined. This needs effort and technique. Man is quite limited in foresight without having experience and lessons from the past. For knowing the risk of an incidental, undesired event both its severity and probability has to be estimated. Then ways to reduce risk become clear. In a process plant risks are many and it is not possible to remove them all. One has to attribute priorities. Intuitive and qualitative methods can do much, but plant complexity may be large and communication on risk may become difficult without formal methodology. Quantitative risk analysis offers much, but has its weaknesses and drawbacks. The required effort is considerable, specialists are needed, and variability in answers is large. Yet, a model built to go along with the life of an installation and updated periodically may be very useful. This paper presents an overview of the demand, problems encountered, possible remedies, and an outlook on useful improvement and extension of risk analysis methodology, including decision making.     

Estimation of the impact probability in domino effects due to the projection of fragments

Despite the remarkable severity of domino effects in activities at major hazard, a complete methodology analysing such events has not been developed and integrated within Quantitative Risk Analysis (QRA). Such a deficiency appears to be particularly remarkable for domino effects triggered by the projection of fragments. The aim of the present work is therefore to propose a systematic procedure for the quantification of domino effects due to fragments projection within QRA. To achieve this objective, the deterministic approach for the estimation of the realistic trajectory of fragments is entirely reviewed. In order to incorporate such a reviewed approach within the standard QRA, a probabilistic model for the impact probability of the fragments is developed by applying a Monte-Carlo method to the trajectory equations. The validation of the proposed framework is carried out by using the data related to an accident occurred in 1993 in the oil refinery of Milazzo (Italy).     

Layer of Protection Analysis – Quantifying human performance in initiating events and independent protection layers

Layer of Protection Analysis (LOPA) is widely used within the process industries as a simplified method to address risks and determine the sufficiency of protection layers. LOPA brings a consistent approach with added objectivity and a greater degree of understanding of the scenarios and risks as compared to purely qualitative studies such as Process Hazard Analyses. LOPA can be used to address a wide range of risk issues and serves as a highly effective aid to decision making.Incorporation of human performance within LOPA is recognized as an important, though often challenging, aspect of the analysis. The human role in potential initiating events or within human independent protection layers is important throughout the process industries, and becomes even more critical for batch processing facilities and in non-routine operations. The human role is key to process safety and the control of risks, necessitating the inclusion and quantification of human actions in independent protection layers for most companies. Human activities as potential initiating events and human performance within independent protection layers are reviewed and methods for quantification outlined. An extension into Human Reliability Analysis (HRA) is provided, including methods to develop Human Error Probabilities specific to the process safety culture and operations at a given plant site.     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process

A new methodology for quantitative risk assessment (QRA) integrated with dynamic simulation and accident simulation is proposed. The objective of this study is to discover inherent risks that are undetectable by conventional risk analysis methods based on steady-state conditions. The target process is the reactor section in the heavy oil desulfurization (HOD) process, which is likely to pose vast potential risks due to the high operating conditions of pressure and temperature. First, a dynamic simulation of a shut-down procedure was performed to observe the behavior of process variables using Aspen HYSYS V10, which is a commercially available process software. Based on the results of the dynamic simulation, several blind spots indicating a higher operating pressure than that in the steady-state simulation were identified. To assess the risks of the detected blind spots, a QRA was performed using the commercial software of SAFETI V8.22, which performs risk calculation based on consequence and frequency data. As a result of applying the proposed method to the HOD process, the risk assessment outcome was identified as intolerably risky unlike that of steady-state conditions, thereby indicating that dynamic simulations can serve as a method to spot inherent risks that are undetectable in steady-state conditions. In addition, mitigation procedures that reduce the risk of the process to a tolerable level are performed, thereby enabling a safer and more reliable process.     

定量风险评价技术在管道城市穿越段的应用

介绍了管道高后果区定量风险评价的方法和风险可接收标准.将定量风险评价技术在我国某长输原油管道城市穿越段的应用表明,定量风险评价方法适用于人口密集的管道高后果区,能对管道高后果区的风险管理、决策提供重要的参考.     

A systemic methodology for risk management in healthcare sector

The recent biomedical, technological, and normative changes have led healthcare organizations to the implementation of clinical governance as a way to ensure the best quality of care in an increasingly complex environment. Risk management is one of the most relevant aspects of clinical governance and approaches put forward in literature highlight the necessity to perform comprehensive analyses intended to uncover root causes of adverse events.Contributing to this field, the present paper applies Reason’s theory of failures to work out a systemic methodology to study risks impacting not only directly but also indirectly on patients. Also, the steps of such approach are organized around Human Reliability Assessment phases, in order to take into account the human component of healthcare systems. This framework is able to foster effective decision making about reducing failures and waste and to improve healthcare organizations’ maturity towards risk management.The developed methodology is applied to the pharmacy department of a large Italian hospital. An extensive validation in different healthcare settings is required to fully prove benefits and limitations.     

Risk-based route evaluation against country-specific criteria of risk tolerability for hazmat transportation through Indian State Highways

Risk-based route evaluation is necessary for decision making by authorities for regulating hazardous materials (hazmats) transport vehicles. The paper highlights risk estimation and its representation for three highway study routes in western India using frequency analysis through logic diagrams and scenario based detailed consequence analysis of accidental releases considering 26 hazmats from UN Classes-2, 3, 6 and 8 categories. The 3 routes have been evaluated based on several layers of analysis namely hazmat-wise, route-segment-wise, route-wise and overall assessment including presentation of normalized risk figures. The results show that compared to the risk on city route segment, individual risks on other two routes are higher and extend beyond ALARP (As Low As Reasonably Practicable) region when assessed against HSE, UK risk criteria, whereas, societal risks on all three routes are within the ALARP except some part in the higher fatality area. But, considering the general mortality rates in India and sustained economic growth, the authors proposed widening of the ALARP region for individual risk tolerability of transportation activity of essential commodities that benefits society to a large extent in this developing economy. However, specific risk reduction measures have also been suggested to improve upon the risk picture in the study area.     

Risk analysis for road and rail transport of hazardous materials: a simplified approach

A simplified approach to transportation risk analysis for road and rail transport of dangerous goods is proposed, which is based on the use of a product databank, containing the impact areas for a number of pre-selected accidental scenarios, and on the selection of a few typical average values of the involved parameters, relevant to the type of transport activity and to the route. Such an approach enables also a non-specialist to very rapidly perform a transportation risk analysis, obtaining both individual and societal risk measures for the study case(s): the results may be used to support a decision making process, and/or as a basis for a more in deep analysis.     

Using risk tolerance criteria to determine safety integrity levels for safety instrumented functions

Standards and industry guidelines for Safety Instrumented Systems (SISs) describe the use of hazard and risk analysis to determine the risk reduction required, or Safety Integrity Levels (SILs), of Safety Instrumented Functions (SIFs) with reference to hazardous events and risk tolerance criteria for them. However, significant problems are encountered when putting this approach into practice. There is ambiguity in the meaning of the term hazardous event. Notably, even though it is a key concept in the process-sector-specific SIS standard, IEC 61511/ISA 84, it is not defined in the standard. Consequently, risk tolerance criteria for hazardous events are ill-defined and, therefore, they are not the most appropriate criteria to use. Most current approaches to SIL determination use them and therefore they are flawed fundamentally.An informed decision on the tolerability of risk for a facility cannot be made by determining only the tolerability of risk for individual hazardous events. Rather, the tolerability of the cumulative risk from all hazard scenarios and their hazardous events for a facility must be determined. Such facility risk tolerance criteria are the type used by regulators. This issue applies to all per event risk tolerance criteria. Furthermore, determining the tolerability of risk for a facility based only on the risks of single events, be they hazard scenarios or hazardous events, and comparing them to risk tolerance criteria for the events is not meaningful because there is no consideration of how many such events can actually occur and, therefore, no measure of the total risk. The risks from events should be summed for a facility and compared with overall facility risk tolerance criteria.This paper describes and illustrates SIL determination using a risk model implemented within the framework of Layers of Protection Analysis (LOPA) that overcomes these problems. The approach allows the allocation of risk across companies, facilities, processes, process units, process modes, etc. to be managed easily.     

A new look at release event frequencies

Within the context of a quantitative risk analysis (QRA), the two main constituents used to describe petrochemical risks are, and have always been, consequence and probability. The consequences of hazardous material accidents are easy to apprehend – if a hazard is realized it can injure people or cause fatalities, damage equipment or other assets, or cause environmental damage. Frequencies for these consequences, on the other hand, are not as easy to understand. Process safety professionals develop event frequencies by evaluating historical data and calculating incident rates, which represent, in the QRA context, how often a release of a hazardous material has occurred. Incident rates are further modified by probabilities for various hole sizes, release orientations, weather conditions, ignition timing, and other factors, to arrive at unique event probabilities that are applied in the QRA. This paper describes the development of incident rates from historical database information for various equipment types, as well as defining a methodology for assigning hole size probabilities from the same data, such that a hole size distribution can be assigned within each QRA study. The combination of total incident rates and a hole size distribution relationship can then serve as a foundation within the frequency side of many QRA studies.     

Reference criteria for the identification of accident scenarios in the framework of land use planning

Land use planning (LUP) around industrial sites at risk of major accidents requires the application of sound approaches in the selection of credible accident scenarios. In fact, the ‘technical’ phase of LUP is based on the identification and assessment of relevant accident scenarios. An improper choice of scenarios may critically affect both the ‘technical’ phase of risk assessment and the following ‘policy’ phase concerning decision making on land-use restrictions and/or licensing. The present study introduces a procedure aimed at the systematic identification of reference accident scenarios to be used in the gathering of technical data on potential major accidents, which is a necessary step for LUP around Seveso sites. Possible accident scenarios are generated by an improved version of the MIMAH methodology (Methodology for the Identification of Major Accident Hazards). The accident scenarios are then assessed for LUP relevance considering severity, frequency and time scale criteria. The influence of prevention and mitigation barriers is also taken into account. Two applications are used to demonstrate the proposed procedure. In both case-studies, the proposed methodology proved successful in producing consistent sets of reference scenarios.