There has been growing public concern regarding the threat to people and environment from industrial activities, thus more rigorous regulations. The investigation of almost all the major accidents shows that we could have avoided those tragedies with effective risk analysis and safety management programs. High-quality risk analysis is absolutely necessary for sustainable development. As a powerful and systematic tool, fault tree analysis (FTA) has been adapted to the particular need of chemical process quantitative risk analysis (CPQRA) and found great applications. However, the application of FTA in the chemical process industry (CPI) is limited. One major barrier is the manual synthesis of fault trees. It requires a thorough understanding of the process and is vulnerable to individual subjectivity. The quality of FTA can be highly subjective and variable. The availability of a computer-based FTA methodology will greatly benefit the CPI. The primary objective of this research is to develop a computer-aided fault tree synthesis methodology for CPQRA. The central idea is to capture the cause-and-effect logic around each item of equipment directly into mini fault trees. Special fault tree models have been developed to manage special features. Fault trees created by this method are expected to be concise. A prototype computer program is provided to illustrate the methodology. Ideally, FTA can be standardized through a computer package that reads information contained in process block diagrams and provides automatic aids to assist engineers in generating and analyzing fault trees. Another important issue with regard to QRA is the large uncertainty associated with available failure rate data. In the CPI, the ranges of failure rates observed could be quite wide. Traditional reliability studies using point values of failure rates may result in misleading conclusions. This dissertation discusses the uncertainty with failure rate data and proposes a procedure to deal with data uncertainty in determining safety integrity level (SIL) for a safety instrumented system (SIS). Efforts must be carried out to obtain more accurate values of those data that might actually impact the estimation of SIL. This procedure guides process hazard analysts toward a more accurate SIL estimation and avoids misleading results due to data uncertainty.

An important objective in statistical risk assessment is estimation of minimum exposure levels, called Benchmark Doses (BMDs) that induce a pre-specified Benchmark Response (BMR) in a target population. Established inferential approaches for BMD analysis typically involve one-sided, frequentist confidence limits, leading in practice to what are called Benchmark Dose Lower Limits (BMDLs). Appeal to hierarchical Bayesian modeling and credible limits for building BMDLs is far less developed, however. Indeed, for the few existing forms of Bayesian BMDs, informative prior information is seldom incorporated. Here, a new method is developed by using reparameterized quantal-response models that explicitly describe the BMD as a target parameter. This potentially improves the BMD/BMDL estimation by combining elicited prior belief with the observed data in the Bayesian hierarchy. Besides this, the large variety of candidate quantal-response models available for applying these methods, however, lead to questions of model adequacy and uncertainty. Facing this issue, the Bayesian estimation technique here is further enhanced by applying Bayesian model averaging to produce point estimates and (lower) credible bounds. Implementation is facilitated via a Monte Carlo-based adaptive Metropolis (AM) algorithm to approximate the posterior distribution. Performance of the method is evaluated via a simulation study. An example from carcinogenicity testing illustrates the calculations.

Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: In the current economic climate where credit crises, fluctuating commodity prices, poor governance, rising unemployment and declining consumer spending exist, risk management is of utmost importance. Proclaiming the existence of a risk management strategy is not enough to ensure that an enterprise achieves its objectives. The implementation of a holistic enterprise-wide risk management framework is required in order to execute strategies and achieve objectives effectively and efficiently Two types of risk management have emerged in industry, namely quantitative and qualitative risk management. On the one hand, qualitative analysis of risk can be done quickly and with minimal effort. However, these methods rely on the opinion of an individual or group of individuals to analyse the risks. The process may be highly subjective and does not fully consider the characteristics of the enterprise. This renders qualitative risk analysis as an ineffective singular strategy although it has been shown to be effective when the risks are well understood. Quantitative analysis, on the other hand, is particularly effective when the risks are not well understood. These methods have been shown to provide substantially more information regarding risks compared to qualitative analysis. However, many quantitative risk management methods presented in literature are studied in isolation and not within the context of a holistic risk management process. Furthermore, quantitative methods tend to be complex in nature and require a reasonable understanding of mathematical and statistical concepts in order to be used effectively. In view of this, there is a need for an enterprise risk management framework that emphasises the use of qualitative methods when the risks are well understood and quantitative methods when in-depth analyses of the risks are required. In this study, a systematic enterprise-wide risk management framework that incorporates both quantitative and qualitative methods was developed. The framework integrates these methods in a logical and holistic manner. The quantitative methods were found be to be largely practical while the qualitative methods presented are simple and easy to understand. / AFRIKAANSE OPSOMMING: In die huidige ekonomiese klimaat waar krediet krisisse, wisselende kommoditeitspryse, swak bestuur, stygende werkloosheid en dalende verbruikersbesteding bestaan, is risikobestuur van die uiterste belang. Die verkondiging van die bestaan van 'n risiko bestuurstrategie is nie genoeg om te verseker dat 'n onderneming sy doelwitte bereik nie. Die implementering van 'n holistiese ondernemings- breë risikobestuursraamwerk is nodig om strategieë en doelwitte doeltreffend en effektief te bereik. Twee tipe risikobestuur het na vore gekom in die bedryf, naamlik kwantitatiewe en kwalitatiewe risikobestuur. Aan die een kant , kan kwalitatiewe ontleding van risiko vinnig en met minimale inspanning gedoen word. Hierdie metode is gewoontlik die mening van 'n individu of 'n groep individue wat die risiko ontleed. Die proses kan hoogs subjektief wees en nie ten volle die eienskappe van die onderneming in ag neem nie. Kwalitatiewe risiko-analise kan dan gesien word as 'n ondoeltreffende enkelvoud strategie maar dit is wel doeltreffend wanneer daar verstaan word wat die onderneming se risiko is. Kwantitatiewe analise, aan die ander kant, is veral effektief wanneer die risiko's nie goed verstaanbaar is nie. Hierdie metode het getoon dat daar aansienlik meer inligting oor die risiko's, in vergelyking met kwalitatiewe ontleding, verskaf word. Daar is egter baie kwantitatiewe risikobestuur metodes wat in literatuur verskaf word, wat in isolasie bestudeer word en nie binne die konteks van 'n holistiese risikobestuur proses nie. Verder is, kwantitatiewe metodes geneig om kompleks van aard te wees en vereis 'n redelike begrip van wiskundige en statistiese konsepte sodat kwantitatiewe analise effektief kan wees. In lig hiervan, is daar 'n sterk behoefte vir 'n onderneming om 'n risikobestuursraamwerk in plek te het. Die risikobestuursraamwerk sal beide die gebruik van kwalitatiewe metodes, wanneer die risiko goed verstaan word, en kwantitatiewe metodes, wanneer daar in diepte-ontledings van die risiko is, beklemtoon. In hierdie studie was 'n sistematiese onderneming-breë risikobestuursraamwerk ontwikkel wat beide kwantitatiewe en kwalitatiewe metodes insluit. Die raamwerk integreer hierdie metodes in 'n logiese en holistiese wyse. Die kwantitatiewe metodes is gevind om grootliks prakties te wees, terwyl die kwalitatiewe metodes wat aangebied word, eenvoudig en maklik is om te verstaan.

Orientadores: Pilar Rodriguez de Massaguer, Amauri Rosenthal / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos / Made available in DSpace on 2018-08-08T21:56:14Z (GMT). No. of bitstreams: 1 Sant'Ana_AndersondeSouza_M.pdf: 2935543 bytes, checksum: 8836bcdf5bfa2652ee4e277718b808dc (MD5) Previous issue date: 2007 / Resumo: A patulina é uma micotoxina produzida por fungos pertencentes aos gêneros Penicillium, Aspergillus e Byssochlamys. Penicillium expansum se destaca por ser potencial produtor de patulina nas maçãs, enquanto Byssochlamys nivea e B.fulva se destacam pela potencial produção desta micotoxina em sucos de maçãs pasteurizados. À patulina tem sido atribuídos diversos efeitos agudos e crônicos adversos à saúde humana. No presente estudo determinou-se quantitativamente o risco dos níveis de patulina no suco de maçã ultrapassar o limite de 50ppb estabelecido pela Organização Mundial de Saúde (OMS) e a probabilidade de produção da patulina por bolores termoresistentes sobreviventes à pasteurização do produto. Para isto, i) avaliou-se a ocorrência de bolores termoresistentes e patulina em amostras pertencentes à 5 diferentes lotes de suco de maçã provenientes de uma unidade produtora localizada no sudeste do Brasil; ii) avaliou-se a capacidade de produção da patulina por cepas de B.fulva (IOC 4518) e B.nivea (ATCC 24008 e FRR 4421) em suco de maçã armazenado à 21ºC e à 30ºC (consideradas temperaturas médias anuais das regiões tropicais e subtropicais do Brasil); iii) determinou-se a cepa Byssochlamys produtora de patulina mais termoresistente dentre as três estudadas, em suco de maçã; iv) determinou-se a resistência térmica através do método dos tubos TDT (thermal death tubes) da cepa mais termoresistente; v) Estabeleceu-se o efeito da pasteurização em sistema contínuo (UHT), simulando as condições industriais, sobre a cepa de Byssochlamys spp mais termoresistente produtora de patulina; vi) determinou-se a probabilidade de produção de patulina pela cepa mais termoresistente produtora de patulina em suco clarificado de maçã variando-se a temperatura de estocagem (21ºC e 30ºC), com carga remanescente pós-processo de 10º e 101 esporos / 100 mL e vii) determinou-se quantitativamente o risco da patulina em suco clarificado de maçã a partir de 15 cenários que relacionados a diferentes cargas de esporos sobreviventes e temperatura de estocagem do suco pós-pasteurização, utilizando-se a modelagem de Monte Carlo, feita através do software @RISK versão 4.5 for students com 1 simulação e 10000 iterações. Os resultados revelaram que a ocorrência de bolores termoresistentes nas amostras de suco de maçã é baixa (<10ºesporos/100mL), com a cepa isolada de (Aspergillus carneus ¿ IOC 4519) não sendo confirmada como um bolor termoresistente. As três cepas estudadas (B.nivea FRR 4421, B.nivea ATCC 24008 e B.fulva IOC 4518) foram capazes de produzir a patulina em concentrações que dependeram da carga de esporos inoculada no suco de maçã, temperatura de estocagem e material de embalagem. B.fulva IOC 4518 foi determinada como a cepa mais termoresistente, sobrevivendo ao choque térmico de 95ºC por 5 min. Valores D* à 85ºC, 90ºC, 92ºC e 95ºC iguais a 64,58 min; 16,68 min; 6,31 min e 3,10 min, respectivamente foram obtidos, enquanto o valor Z foi igual a 7,4ºC. O processo de pasteurização do suco de maçã na unidade Microthermics mostrou que há variabilidade com relação ao número de reduções causadas pelo processo equivalente ao industrial quando variações na temperatura de processo da ordem de até 1ºC são observadas. Maiores probabilidades de crescimento de B.fulva IOC 4518 e maior extensão da deterioração no suco de maçã estão relacionadas ao aumento da carga de esporos sobreviventes e temperatura de estocagem pós-processo. A produção de patulina por B.fulva IOC 4518 é influenciada principalmente pela temperatura de estocagem quando a carga de sobreviventes é elevada (101esporos/100mL), com maiores quantidades da micotoxina sendo produzidas à 30ºC do que à 21ºC. Através do modelo de risco para o suco de maçã e patulina pôde-se concluir que a etapa de recepção é sempre a que mais impactou para que níveis elevados de patulina estejam presentes nos sucos de maçã. Mas, a etapa de estocagem após a pasteurização quando há bolores termoresistentes sobreviventes, foi a responsável pelas maiores concentrações finais de patulina, à medida que se aumentava o tempo de estocagem. As etapas de lavagem, filtração e seleção das frutas, respectivamente, são as responsáveis pela redução nos níveis de patulina durante o processamento do suco, enquanto a pasteurização em virtude da elevada resistência térmica desta micotoxina praticamente não apresenta efeito algum para redução dos níveis da micotoxina no produto final. Após 10000 iterações, dentre os 15 cenários avaliados, somente nos de número 1 (sem sobreviventes à pasteurização e concentração de patulina na matéria-prima na faixa baixa), 2 (sem sobreviventes à pasteurização e concentração de patulina na matéria-prima na faixa média), 4 (10ºesporos/100mL de B.fulva IOC 4518 sobreviventes à pasteurização, com temperatura de estocagem de 21ºC e concentração de patulina na matéria-prima na faixa baixa) e 7 (10ºesporos/100mL de B.fulva IOC 4518 sobreviventes à pasteurização, com temperatura de estocagem de 30ºC e concentração de patulina na matéria-prima na faixa baixa) o limite de 50ppb de patulina não seria ultrapassado para nenhuma das iterações, considerando-se valores médios e máximos da concentração final desta micotoxina. A distribuição da concentração de patulina no produto final se ajustou às distribuições do tipo Betageneral, Lognormal e Inversa Gaussiana dependendo da concentração de patulina na recepção das frutas, com a média e a maior parte dos dados se concentrando à esquerda / Abstract: Patulin is a mycotoxin produced by some species from Penicillium, Aspergillus and Byssochlamys ssp genera. Penicillium expansum are known by their potential to produce patulin in apples, while Byssochlamys nivea and B.fulva are recognized by its potential to produce this micotoxin in pasteurized apple juice. Several acute and chronic effects to human health have been attributed to patulin. This study has quantitatively assessed the risk of levels of patulin to exceed the level established by The World Health Organization ¿ WHO (50ppb) and also was determined the probability of patulin being produced by heat-resistant mold which survived the apple juice pasteurization. Therefore, the following items have been analyzed: i) it was evaluated the occurrence of heat resistant mold and patulin in samples belonging to 5 different lots of apple juice from a factory located in the southeast of Brazil; ii) the ability of patulin production by the strains of B.fulva (IOC 4518) and B.nivea (ATCC 24008 and FRR 4421) in apple juice stored at 21°C and 30°C (these are average year temperature in the tropical and subtropical regions of Brazil); iii) it was determined which of the three patulin producer strains, B. fulva and/or B.nivea, was the most heat resistant in apple juice; iv) it was determined the heat resistance (D and Z values) of the most heat resistant patulin producer strain of Byssochlamys using thermal death tubes (TDT); v) the effect of the continuous pasteurization system (UHT), simulating the industrial conditions, has been established over the most heat resistant and patulin producer strain of Byssochlamys spp; vi) the probability of producing patulin by the most heat resistant strain in clarified apple juice stored at 21°C and 30°C with a survival level post pasteurization process of 10º e 101 spores/100 mL, has also been established. vii) it has been quantitatively assessed the risk of patulin in clarified apple juice using Monte Carlo simulation, with @Risk software for students (version 4.5). The simulation was carried out with 10000 iterations. The results showed that the occurrence of heat resistant mold in the apple juice samples examined was low (<10ºesporos/100mL), with the strain Aspergillus carneus ¿ IOC 4519 isolated not confirming their heat resistance. The three mold strains studied (B.nivea FRR 4421, B.nivea ATCC 24008 and B.fulva IOC 4518) were able to produce patulin in concentrations that were dependent of spore inocula in apple juice, storage temperature and package type. B.fulva IOC 4518 was determined as the most heat resistant strain, surviving to heat shock at 95ºC/5 min. D* values at 85ºC, 90ºC, 92ºC and 95ºC of 64,58 min; 16,68 min; 6,31 min and 3,10 min, respectively were obtained, while z value was of 7.4ºC. The apple juice pasteurization process applied in a Microthermics pilot plant showed variability related to the number of decimal reductions caused by the equivalent process when temperature variations were near 1ºC. Higher growth probabilities for B.fulva IOC 4518 and higher extension of spoilage of apple juice are related to the increase of survival spore level and to storage temperature pos-pasteurization. The patulin production by B.fulva IOC 4518 was mainly influenced by storage temperature when survival spores level is elevated (101spores/100mL), with the higher quantities of this mycotoxin being produced at 30ºC than 21ºC. The risk assessment model for the apple juice and patulin showed that fruit reception is always the step that more impacted to higher levels of patulin being found in apple juices. However, storage step after pasteurization, when there are heat resistant survivors was responsible for the higher final concentrations, when the storage time increased. Fruit washing, juice filtration and fruit selection, respectively, are the main responsible steps to reduce patulin levels during apple juice processing, while juice pasteurization due to high heat resistance of patulin practically does not presents effects on mycotoxin reduction in the final product. After 10000 iterations, among the 15 scenarios evaluated, only in the scenario number 1 (without mold survival to pasteurization and with low level of patulin concentration in fruits), 2 (without mold survival to pasteurization and with medium level of patulin concentration in fruits), 4 (10º/100mL of B.fulva IOC 4518 spores survival to pasteurization, with storage temperature at 21ºC and low level of patulin in fruits) and 7 (10º/100mL of B.fulva IOC 4518 spores survival to pasteurization, with storage temperature at 30ºC and low level of patulin in fruits) the limit of 50ppb of patulin would not be exceeded for any of iterations, considering medium and maximum values of the final quantity of this mycotoxin. The final distribuition of patulin concentration in apple juice best fitted to Betageneral, Lognormal and Inverse Gaussian depending on the concentration on fruit reception, with the mean and the most part of data skewed to the left / Mestrado / Mestre em Ciência de Alimentos

The usage of information systems (IS) within organizations has become crucial. Information is one of the most vulnerable resources within an enterprise. Information can be exposed, tampered or made non-accessible, where the integrity, confidentiality or availability becomes affected. The ability to manage risks is therefore a central issue in enterprises today. In order to manage risks, the risks need to be identified and further evaluated. All kind of threats with the possibility to negatively affect the confidentiality, integrity, or availability of the organization need to be reviewed. The process of identifying and estimating risks and possible measures is called risk analysis. There are two main categories of risk analysis, qualitative and quantitative. A quantitative method involves interpreting numbers from data and is based on objective inputs. A qualitative method involves interpreting of subjective inputs such as brainstorming and interviews. A common approach is to apply a qualitative method, however a lot of criticism has been raised against using subjective inputs to assessing risks. Secure State is a consulting company with specialist expertise in the field of information security. They help their customers to build trust in the customers systems and processes, making their customers businesses operate with consideration to information security. One service offered by Secure State is risk analysis, and currently they perform qualitative risk analysis. Given all criticisms against a qualitative approach for assessing risks, this study developed a quantitative risk analysis method for Secure State. According to participants, who attended at a risk analysis where the developed quantitative risk analysis method was used, the quantitative risk analysis method improved the risk assessment. Since risks and their effects are decomposed into smaller components in the proposed quantitative risk analysis method, interpretations of risks and their meaning during assessments less likely differed. Therefore, the common understanding of a risk increases, which makes the quality of the evaluation of risks increase. Furthermore, the usage of statistical data increases in the developed quantitative risk analysis method. Additionally, the quantitative method handles the fact that all data used is imperfect. The data is imperfect since it is used to describe the future, and the future has not happened yet.

It is well known that for highly skewed distributions the standard method of using the t statistic for the confidence interval of the mean does not give robust results. This is an important problem for importance sampling (IS) as its final distribution is often skewed due to a heavy tailed weight distribution. In this paper, we first explain Hall's transformation and its variants to correct the confidence interval of the mean and then evaluate the performance of these methods for two numerical examples from finance which have closed-form solutions. Finally, we assess the performance of these methods for credit risk examples. Our numerical results suggest that Hall's transformation or one of its variants can be safely used in correcting the two-sided confidence intervals of financial simulations.(author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Quantitative risk analysis (QRA) is widely applied in several industries as a tool to improve safety, as part of design, licensing or operational processes. Nevertheless, there is much less academic research on the validity and validation of QRA, despite their importance both for the science of risk analysis and with respect to its practical implication for decision-making and improving system safety. In light of this, this paper presents a review focusing on the validity and validation of QRA in a safety context. Theoretical, methodological and empirical contributions in the scientific literature are reviewed, focusing on three questions. Which theoretical views on validity and validation of QRA can be found? Which features of QRA are useful to validate a particular QRA, and which frameworks are proposed to this effect? What kinds of claims are made about QRA, and what evidence is available for QRA being valid for the stated purposes? A discussion follows the review, focusing on the available evidence for the validity of QRA and the effectiveness of validation methods.

A risk assessment study is conducted in a denim manufacturing plant in Turkey. The study is carried out within the framework of a project on adopting the Integrated Pollution Prevention and Control (IPPC) Directive of the European Union. The scope of the assessment is fire or explosion risk with regards to hazardous chemicals present in the plant. The receptor of the study is defined as &ldquo / people&rdquo / which include the employees in the plant, employees of nearby plants and people in residential around the mill. A semi-quantitative risk assessment is carried out using checklist, a risk matrix and risk evaluation forms. The highest risks in the plant are identified as dust explosions, natural gas jet fires, natural gas explosions. Also, it is identified that due to several causes, in case of a fire or explosion the scale of an accident may enlarge instantaneously. The main warehouse is determined to carry the highest risk value in the plant. Mathematical modelling studies are conducted to calculate the hazard radius for dust explosions and natural gas fire and explosion. According to the results of mathematical modelling, the highest consequences could lead to destruction of buildings or severe injuries/fatalities of people within large hazard radius up to 700 m. The risk present at the manufacturing mill is communicated to the facility management throughout the study. Several suggestions are proposed to the facility management and some of them are already implemented.

Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. Uncertainty has been identified as a contributing factor in late projects. This uncertainty resides in activity duration estimates, unplanned upsetting events, and the potential unavailability of critical resources. This research developed a comprehensive simulation based methodology for conducting quantitative project completion-time risk assessments. The methodology enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used to determine a project's completion distribution function. The project simulation is populated with both deterministic and stochastic elements. Deterministic inputs include planned activities and resource requirements. Stochastic inputs include activity duration growth distributions, probabilities for unplanned upsetting events, and other dynamic constraints upon project activities. Stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Multiple replications of the simulation are run to create the completion distribution function. The methodology was demonstrated to be effective for the on-going project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. Project stakeholders participated in determining and managing completion distribution functions. The first result was improved project completion risk awareness. Secondly, mitigation options were analyzed to improve project completion performance and reduce total project cost.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24212号 / 工博第5040号 / 新制||工||1787(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 中北 英一, 准教授 山口 弘誠, 准教授 佐山 敬洋 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM