At present there is no simple, yet scientifically robust method for calculating insurance loss estimates due to a fire. Therefore building owners and insurers can not make suitably informed decisions when selecting fire protection measures or setting premiums as they have no way of defining the true risk they face. As a consequence this research aims to investigate a number of techniques in an effort to define one as appropriate for further research. Three different methods were explored and consist of risk based analysis, deterministic hand calculations and Computational Fluid Dynamics (CFD). Extensive literature reviews were conducted in each area and the final models were based on the outcomes of this research. Rack storage warehouses were chosen for analysis as they are currently topical within the fire engineering community and are a particular concern for insurers. The risk based analysis employed statistical techniques including event tree analysis and monte carlo simulation to calculate loss distributions and sensitivity analyses. The hand calculation method was based on equations presented in the literature and incorporated the use of a zone model (BRANZFire) to calculate deterministic loss estimates. The CFD model used was Fire Dynamics Simulator and full scale warehouse fires were modelled using this programme. It was concluded that Fire Dynamics Simulator is an inappropriate tool as the capability for providing loss estimates in a timely manner is currently beyond the model's capabilities. Of the two remaining methods the statistical risk based model was selected as the most appropriate for further investigation. The primary reasons for this decision were the ability to calculate loss distributions and conduct sensitivity analyses, as well as its versatility and user friendliness. Improved statistical data was defined as imperative for future development of the model.

All individuals are unique in their characteristics. As such, their positive and negative contributions to system performance differ. In any system that is not fully automated, the effect of the human participants has to be considered when one is interested in the performance optimization of the system. Humans are intelligent, adaptive, and learn over time. At the same time, humans are error-prone. Therefore, in situations where human and hardware have to interact and complement each other, the system faces advantages and disadvantages from the role the humans play. It is this role and its effect on performance that is the focus of this dissertation. When analyzing the role of people, one can focus on providing resources to enable the human participants to produce more. Alternatively, one can strive to ensure the occurrence of less frequent and impactful errors. The focus of the analysis in this dissertation is the latter. Our analysis can be categorized into two parts. In the first part of our analysis, we consider a short term planning horizon and focus directly on failure risk analysis. What can be done about the risk stemming from the human participant? Any proactive steps that can be taken will have the advantage of reducing risk, but will also have a cost associated with it. We develop a cost-benefit analysis to enable a decision-maker to choose the optimal course of action for revenue maximization. We proceed to use this model to calculate the minimum acceptable level of risk, and the associated skill level, to ensure system profitability. The models developed are applied to a case study that comes from a manufacturing company in Ontario, Canada. In the second part of our analysis, we consider a longer planning horizon and are focused on output maximization. Human learning, and its effect on output, is considered. In the first model we develop, we use learning curves and production forecasting models to optimally assign operators, in order to maximize system output. In the second model we develop, we perform a failure risk analysis in combination with learning curves, to forecast the total production of operators. Similar to the first part of our analysis, we apply the output maximization models to the aforementioned case study to better demonstrate the concepts.

All individuals are unique in their characteristics. As such, their positive and negative contributions to system performance differ. In any system that is not fully automated, the effect of the human participants has to be considered when one is interested in the performance optimization of the system. Humans are intelligent, adaptive, and learn over time. At the same time, humans are error-prone. Therefore, in situations where human and hardware have to interact and complement each other, the system faces advantages and disadvantages from the role the humans play. It is this role and its effect on performance that is the focus of this dissertation. When analyzing the role of people, one can focus on providing resources to enable the human participants to produce more. Alternatively, one can strive to ensure the occurrence of less frequent and impactful errors. The focus of the analysis in this dissertation is the latter. Our analysis can be categorized into two parts. In the first part of our analysis, we consider a short term planning horizon and focus directly on failure risk analysis. What can be done about the risk stemming from the human participant? Any proactive steps that can be taken will have the advantage of reducing risk, but will also have a cost associated with it. We develop a cost-benefit analysis to enable a decision-maker to choose the optimal course of action for revenue maximization. We proceed to use this model to calculate the minimum acceptable level of risk, and the associated skill level, to ensure system profitability. The models developed are applied to a case study that comes from a manufacturing company in Ontario, Canada. In the second part of our analysis, we consider a longer planning horizon and are focused on output maximization. Human learning, and its effect on output, is considered. In the first model we develop, we use learning curves and production forecasting models to optimally assign operators, in order to maximize system output. In the second model we develop, we perform a failure risk analysis in combination with learning curves, to forecast the total production of operators. Similar to the first part of our analysis, we apply the output maximization models to the aforementioned case study to better demonstrate the concepts.

The model building and fire codes in Canada permit prescriptive-based design and performance-based design approaches. Within this regulatory framework, prescriptive-based designs are attributed objective and functional statements to qualify the level of fire protection and life safety required. Performance-based designs, or alternative solutions to prescriptive-based designs, must be demonstrated to achieve at least an equivalent level of performance as the prescriptive requirement based on evaluation of each associated objective and functional statement. Due to the qualitative performance descriptions available, the current system for developing and reviewing alternative solutions is vulnerable to the acceptance of over-designed or under-designed life safety and fire protection measures in buildings. The objective of this thesis is to establish a method to compare the performance of alternative solutions with prescriptive design requirements on a quantitative basis. This thesis generates eight objectives for a fire risk analysis tool to address the challenges identified in the building regulatory industry. Based on review of existing techniques, a new fire risk analysis framework is developed. The Quantitative Design Decision (QDD) method, integrates risk analysis with quantitative decision assessment techniques to facilitate application-specific quantification of performance objectives and to aid evaluation of performance-based designs. The method utilizes an iterative three-stage structure. To demonstrate the application of the QDD method, a case-study simulation has been conducted. The case-study provides an evaluation of alternative designs to the prescriptive requirements for explosion-relief ventilation in rooms housing flammable vapour producing operations. The case study supports the conclusion that QDD achieves the eight objectives set out in this thesis. For validation, the QDD method must be applied to a wider variety of practical design challenges and it is recommended that the results be considered in conjunction with live fire test data to verify key aspects of the performance decisions generated. Future work should include evaluation of Delphi technique application in the Design Decision Stage of the QDD method. It is proposed that the method developed can be extended for use as a general performance-based design tool.

In development projects, designers should take into consideration the possibility of a vapor cloud explosion in the siting and design of a process plant from day one. The most important decisions pertinent to the location of different process areas, separation between different areas, location of occupied buildings and overall layout may be made at the conceptual stage of the project. During the detailed design engineering stage the final calculation of gas explosion loads is an important activity. However, decisions related to the layout and location of occupied buildings at this stage could be very costly. Therefore, at the conceptual phase of the development project for a hydrocarbon facility, it would be helpful to get a picture of possible vapor cloud explosion loads to be used in studying various options. This thesis presents the analytical parameters that are used in vapor cloud explosion risk analysis. It proposes a model structure for the analysis of vapor cloud explosion risks to buildings based on exceedance methodology. This methodology was developed in a computer program which is used to support this thesis. The proposed model considers all possible gas release scenarios through the use of the Monte Carlo simulation. The risk of vapor cloud explosions can be displayed using exceedance curves. The resulting model provides a predictive tool for vapor cloud explosion problems at the early stages of development projects, particularly in siting occupied buildings in onshore hydrocarbon facilities. It can also be used as a quick analytical tool for investigating various aspects of vapor cloud explosions. This model has been applied to a case study, a debutanizer process unit. The model was used to explore the different alternatives of locating a building near the facility. The results from the model were compared to the results of other existing software to determine the model validity. The results show that the model can effectively examine the risk of vapor cloud explosions.

Risk analysis using likelihood or probability and consequence (L x C) is prone to both methodological and application errors. This contributes to difficulties in achieving risk reduction. As an alternative to the L x C model, this study reviews risk and control effectiveness within the Australian extractive minerals industry. It draws on existing models, locally and internationally, and their application in other industry contexts. The study contends that control effectiveness is more useful and beneficial than L x C alone in determining ‘acceptable’ risk. This hypothesis is substantiated by the development of an alternative model, Major Accident Control Analysis (MACA), based around the prevention of fatalities by exploring and quantifying the following control parameters: 1) controls pre and/or post event, 2) the control type, and 3) the effectiveness of the specific control. By assigning these control parameters, discrete values, comparisons between individual ‘risk’ scenarios and established numerical acceptability risk criteria are possible. The theoretical proposition of this research was tested using detailed case studies to highlight the flaws of conventional risk analysis and, instead, accentuate control effectiveness as a superior method for prioritising risk and determine acceptability. The results of the research demonstrate that control effectiveness, utilised by the MACA method, is particularly valuable when limited data is available to permit quantification, data is too generalised for the operating conditions and where qualitative risk estimates are insufficient and inappropriate to prevent fatalities. MACA employs mathematically valid algorithms previously not envisaged nor developed by earlier methodologies. Importantly, these algorithms enable an interchangeable conversion of control effectiveness ‘values’ to risk ‘values’. Beyond the immediate findings of the research, the additional benefits of control effectiveness are multiple. The principles are suitable to the dynamic nature of the minerals industry, yet are highly adaptable and can be readily applied beyond the field of mining. The methodology could be applied to any circumstance where traditional risk analysis is typically undertaken, thus demonstrating broader application and significance. Furthermore, the methodology is compatible with, and complementary to, existing risk approaches. The intrinsic flexibility offered by this alternative method makes provision for international variations of risk criteria used to determine ‘acceptability’. It is thus determined that the application of control effectiveness estimation offers benefits over and beyond those currently employed.

The Subsea blowout preventer (BOP) which is latched to a subsea wellhead is one of several barriers in the well to prevent kicks and blowouts and it is the most important and critical equipment, as it becomes the last line of protection against blowout. The BOP system used in Subsea drilling operations is considered a Safety – Critical System, with a high severity consequence following its failure. Following past offshore blowout incidents such as the most recent Macondo in the Gulf of Mexico, there have been investigations, research, and improvements sought for improved understanding of the BOP system and its operation. This informs the need for a systematic re-evaluation of the Subsea BOP system to understand its associated risk and reliability and identify critical areas/aspects/components. Different risk analysis techniques were surveyed and the Failure modes effect and criticality analysis (FMECA) selected to be used to drive the study in this thesis. This is due to it being a simple proven cost effective process that can add value to the understanding of the behaviours and properties of a system, component, software, function or other. The output of the FMECA can be used to inform or support other key engineering tasks such as redesigning, enhanced qualification and testing activity or maintenance for greater inherent reliability and reduced risk potential. This thesis underscores the application of the FMECA technique to critique associated risk of the Subsea BOP system. System Functional diagrams was developed with boundaries defined, a FMECA were carried out and an initial select list of critical component failure modes identified. The limitations surrounding the confidence of the FMECA failure modes ranking outcome based on Risk priority number (RPN) is presented and potential variations in risk interpretation are discussed. The main contribution in this thesis is an innovative framework utilising Multicriteria decision making (MCDA) analysis techniques with consideration of fuzzy interval data is applied to the Subsea BOP system critical failure modes from the FMECA analysis. It utilised nine criticality assessment criteria deduced from expert consultation to obtain a more reliable ranking of failure modes. The MCDA techniques applied includes the technique for order of Preference for similarity to the Ideal Solution (TOPSIS), Fuzzy TOPSIS, TOPSIS with interval data, and Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE). The outcome of the Multi-criteria analysis of the BOP system clearly shows failures of the Wellhead connector, LMRP hydraulic connector and Control system related failure as the Top 3 most critical failure with respect to a well control. The critical failure mode and components outcome from the analysis in this thesis is validated using failure data from industry database and a sensitivity analysis carried out. The importance of maintenance, testing and redundancy to the BOP system criticality was established by the sensitivity analysis. The potential for MCDA to be used for more specific analysis of criteria for a technology was demonstrated. Improper maintenance, inspection, testing (functional and pressure) are critical to the BOP system performance and sustenance of a high reliability level. Material selection and performance of components (seals, flanges, packers, bolts, mechanical body housings) relative to use environment and operational conditions is fundamental to avoiding failure mechanisms occurrence. Also worthy of notice is the contribution of personnel and organisations (by way of procedures to robustness and verification structure to ensure standard expected practices/rules are followed) to failures as seen in the root cause discussion. OEMs, operators and drilling contractors to periodically review operation scenarios relative to BOP system product design through the use of a Failure reporting analysis and corrective action system. This can improve design of monitoring systems, informs requirement for re-qualification of technology and/or next generation designs. Operations personnel are to correctly log in failures in these systems, and responsible Authority to ensure root cause analysis is done to uncover underlying issue initiating and driving failures.

Programa de Pós-Graduação em Engenharia Geotécnica. Núcleo de Geotecnia, Escola de Minas, Universidade Federal de Ouro Preto. / Submitted by Maurílio Figueiredo (maurilioafigueiredo@yahoo.com.br) on 2013-02-25T22:46:43Z No. of bitstreams: 1 DISSERTAÇÃO_AnáliseGestãoRiscos.pdf: 4810828 bytes, checksum: 80befbd09bae6bc93ea2045d64dfc2eb (MD5) / Approved for entry into archive by Neide Nativa (neide@sisbin.ufop.br) on 2013-03-13T19:22:34Z (GMT) No. of bitstreams: 1 DISSERTAÇÃO_AnáliseGestãoRiscos.pdf: 4810828 bytes, checksum: 80befbd09bae6bc93ea2045d64dfc2eb (MD5) / Made available in DSpace on 2013-03-13T19:22:35Z (GMT). No. of bitstreams: 1 DISSERTAÇÃO_AnáliseGestãoRiscos.pdf: 4810828 bytes, checksum: 80befbd09bae6bc93ea2045d64dfc2eb (MD5) Previous issue date: 2012 / Oliveira, Marcelo Tuler de / A presente dissertação discute a crescente problemática do risco em nosso atual paradigma tecnológico, sua percepção e tolerabilidade, assim como a ocupação desordenada das faixas de servidão de linhas de transmissão pela sociedade. A hipótese fundamental que enfatiza uma Gestão de Riscos, metodologia da engenharia, é a que se refere à observância e aplicação de técnicas preventivas aos perigos e riscos distribuídos entre grupos sociais mais vulneráveis, geralmente pobres e minorias, acarretados pelas relações ambientais, sistemas de produção e à vida moderna, especificamente na relação da exposição a campos eletromagnéticos e riscos a saúde. Portanto, o trabalho tem o objetivo de focar um determinado cenário, tratando o percentual de pessoas que residem em áreas próximas a linhas de transmissão de energia elétrica do município de Belo Horizonte, estado de Minas Gerais, Brasil, aplicando-se o SIG – Sistema de Informação Geográfica, que facilita a análise espacial desta ocupação, bem como os demais itens correlacionados. As informações sobre as linhas de transmissão foram fornecidas pela concessionária de energia elétrica local. Dados demográficos e socioeconômicos foram obtidos do IBGE e prefeitura local. Algumas imagens, fotos e mapas foram obtidos do acervo do município, através da URBEL, além de levantamento de campo. Através desse levantamento, foi possível identificar a população potencialmente exposta aos riscos e as diversas características para o estudo. Esses corredores incluíram a população residente exposta aos riscos da Linha de Transmissão de um bairro, cuja denominação é Vila Alta Tensão. Através da análise, o estudo comprovou que a população de maior vulnerabilidade, possui baixos índices de renda, escolaridade e desconhece a gravidade dos riscos, bem como não se preocupam com o fato de conviver com este risco. ________________________________________________________________________________________________ABSTRACT: This paper discusses the growing problem of risk in our current technological paradigm, its perception and tolerability, as well as disorderly bands of servitude of transmission lines by society. The fundamental hypothesis that emphasizes risk management, engineering methodology, it is referred to the observance and application of preventive techniques for hazards and risks distributed among most vulnerable social groups, generally poor and minorities, brought on by environmental relationships, production systems and modern life, specifically in search for answers about the relationship between exposure to electromagnetic fields and health risks. Therefore, the work aims to focus on a particular scenario, dealing with the percentage of persons residing in areas close to transmission lines of electricity in the city of Belo Horizonte, Minas Gerais, Brazil, applying GIS - System Geographic Information, facilitates the spatial analysis of this occupation, as well as other related items. Information on the transmission lines were provided by the local electric utility. Demographic and socioeconomic data were obtained the IBGE and local council. Some images, photos and maps were obtained from the collection of the municipality, by Urbel, and field survey. Through this survey, it was possible to identify the population potentially exposed to various risks and characteristics for the study. These corridors included the population exposed to the risks of transmission line of a neighborhood whose name is Vila High Voltage. Through analysis, the study found that the population most vulnerable, have low levels of income, education and unaware of the seriousness of the risks and do not care about the fact to live with this risk.

xv, 178 p. : ill. A print copy of this title is available through the UO Libraries under the call number: KNIGHT HM1101 .D54 2007 / The main goal of many political and intelligence forecasts is to effectively communicate risk information to decision makers (i.e. consumers). Standard reporting most often consists of a narrative discussion of relevant evidence concerning a threat, and rarely involves numerical estimates of uncertainty (e.g. a 5% chance). It is argued that numerical estimates of uncertainty will lead to more accurate representations of risk and improved decision making on the part of intelligence consumers. Little work has focused on how well consumers understand and use forecasts that include numerical estimates of uncertainty. Participants were presented with simulated intelligence forecasts describing potential terrorist attacks. These forecasts consisted of a narrative summary of the evidence related to the attack and numerical estimates of likelihood and potential harm. The primary goals were to explore how the structure of the narrative summary, the format of likelihood information, and the numerical ability (numeracy) of consumers affected perceptions of intelligence forecasts. Consumers perceived forecasts with numerical estimates of likelihood and potential harm as more useful than forecasts with only a narrative evidence summary. However, consumer's risk and likelihood perceptions were more greatly affected by the narrative evidence summary than the stated likelihood information. These results show that even "precise" numerical estimates of likelihood are not necessarily evaluable by consumers and that perceptions of likelihood are affected by supporting narrative information. Numeracy also moderated the effects of stated likelihood and the narrative evidence summary. Consumers higher in numeracy were more likely to use the stated likelihood information and consumers lower in numeracy were more likely to use the narrative evidence to inform their judgments. The moderating effect of likelihood format and consumer's perceptions of forecasts in hindsight are also explored. Explicit estimates of uncertainty are not necessarily useful to all intelligence consumers, particularly when presented with supporting narrative evidence. How consumers respond to intelligence forecasts depends on the structure of any supporting narrative information, the format of the explicit uncertainty information, and the numerical ability of the individual consumer. Forecasters should be sensitive to these three issues when presenting forecasts to consumers. / Adviser: Paul Slovic

Empresas em todo o mundo têm atingido um melhor desempenho operacional com a implantação da Produção Enxuta (IPE), apesar de que os resultados são frequentemente aquém do esperado, demorados a alcançar ou difíceis de sustentar em longo prazo. Tais fatos indicam a necessidade de aprofundar o conhecimento sobre as dificuldades no processo de IPE. Nesta pesquisa, as dificuldades na IPE são reinterpretadas e investigadas sob a perspectiva da Gestão de Riscos (GR), uma vez que isso induz à gestão sistemática dos mesmos sob a lógica PDCA e um amplo entendimento do contexto onde elas ocorrem. O objetivo geral desta pesquisa foi desenvolver um método para avaliação dos riscos na IPE. A estrutura da pesquisa foi dividida em cinco artigos, com os seguintes métodos e propósitos: 1) uma revisão sistemática da literatura para identificar o estado da arte sobre a IPE e propor uma agenda para pesquisas futuras; 2) uma survey e um estudo de caso para identificar e validar a lista dos principais riscos presentes na IPE e a existência de relações entre os riscos; 3) uma revisão bibliográfica para criar uma sistemática para a GR na IPE com o objetivo de desenvolver procedimentos para as etapas de descrição do contexto e avaliação dos riscos; 4) aplicar em um estudo de caso as etapas de descrição do contexto e análise dos riscos, sendo que estas fazem parte da avaliação dos riscos; 5) um estudo de caso enfatizando as etapas de análise e modelagem das relações entre os riscos. As principais contribuições da tese consistem em desenvolver e testar um método para a avaliação de riscos na IPE, identificar e descrever as características dos principais riscos na IPE e criar procedimentos para a análise e modelagem das relações entre os riscos. / Companies worldwide have improved operational performance by lean production implementation (LPI), although the results are often lesser than expected, long reach or difficult to sustain in the long term. These facts indicate a need to increase knowledge of the difficulties in the LPI process. In this research, the difficulties in LPI are reinterpreted and investigated with the risk management (RM) perspective, since it leads to systematic management under the PDCA logic and a broad understanding of the context. The main objective of this thesis was to develop a method for risk assessment in LPI. The structure of the research was divided into five articles, with the following methods and purposes: 1) a systematic literature review to identify the state of the art on the LPI and propose an agenda for future research; 2) a survey and a case study to identify and validate the list of major risks present in the LPI and the existence of relationships between risks; 3) a literature review to create a framework of RM on the LPI in order to develop procedures for the steps of the context description and assessment of risks; 4) apply in a case study the steps of description of the context and risk analysis, as part of the risk assessment; 5) a case study highlighting the steps of risk analysis and risk evaluations by modeling of the relationships between risks. The main contributions of the thesis are to develop and test a method for risk assessment in LPI, identify and describe the characteristics of the main risks in LPI and create procedures for risk identification, analysis and evaluation, the three steps of risk assessment.