京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第17885号 / 工博第3794号 / 新制||工||1580(附属図書館) / 30705 / 京都大学大学院工学研究科航空宇宙工学専攻 / (主査)教授 藤本 健治, 教授 泉田 啓, 教授 椹木 哲夫 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Yes / Flaring is a combustion process commonly used in the oil and gas industry to dispose flammable waste gases. Flare flameout occurs when these gases escape unburnt from the flare tip causing the discharge of flammable and/or toxic vapor clouds. The toxic gases released during this process have the potential to initiate safety hazards and cause serious harm to the ecosystem and human health. Flare flameout could be caused by environmental conditions, equipment failure, and human error. However, to better understand the causes of flare flameout, a rigorous analysis of the behavior of flare systems under failure conditions is required. In this article, we used fault tree analysis (FTA) and the dynamic Bayesian network (DBN) to assess the reliability of flare systems. In this study, we analyzed 40 different combinations of basic events that can cause flare flameout to determine the event with the highest impact on system failure. In the quantitative analysis, we use both constant and time-dependent failure rates of system components. The results show that combining these two approaches allows for robust probabilistic reasoning on flare system reliability, which can help improving the safety and asset integrity of process facilities. The proposed DBN model constitutes a significant step to improve the safety and reliability of flare systems in the oil and gas industry.

Real-world processes often undergo improvements to meet certain goals, such as coping with changed requirements, eliminating defects, improving the quality of the products, and reducing costs. Identifying and evaluating the defects or errors in the process, identifying the causes of such defects, and validating proposed improvements all require careful analysis of the process.Human-intensive processes, where human contributions require considerable domain expertise and have a significant impact on the success or failure of the overall mission, are of particular concern because they can be extremely complex and may be used in critical, including life-critical, situations. To date, the analysis support for such processes is very limited. If done at all, it is usually performed manually and can be extremely time-consuming, costly and error-prone.There has been considerable success lately in using static analysis techniques to analyze hardware systems, software systems, and manufacturing processes. This thesis explores how such analysis techniques can be automated and employed to effectively analyze life-critical, human-intensive processes. In this thesis, we investigated two static analysis techniques: Finite-State Verification (FSV) and Fault Tree Analysis (FTA). We proposed a process analysis framework that is capable of performing both FSV and FTA on rigorously defined processes. Although evaluated for processes specified in the Little-JIL process definition language, this is a general framework independent of the process definition language. For FSV, we developed a translation-based approach that is able to take advantage of existing FSV tools. The process definition and property to be evaluated are translated into the input model and property representation accepted by the selected FSV tool. Then the FSV tool is executed to verify the model against the property representation. For FTA, we developed a template-based approach to automatically derive fault trees from the process definition. In addition to showing the feasibility of applying these two techniques to processes, much effort has been put on improving the scalability and the usability of the framework so that it can be easily used to analyze complex real-world processes. To scale the analysis, we investigated several optimizations that are able to dramatically reduce the translated models for FSV tools and speed up the verification. We also developed several optimizations for the fault tree derivation to make the generated fault tree much more compact and easier to understand and analyze. To improve the usability, we provided several approaches that make analysis results easier to understand. We evaluated this framework based on the Little-JIL process definition language and employed it to analyze two real-world, human-intensive processes: an in-patient blood transfusion process and a chemotherapy process. The results show that the framework can be used effectively to detect defects in such real-world, human-intensive processes.

Yes / Internet of Things (IoT)-based smart agriculture systems are increasingly being used to improve agricultural yield. IoT devices used for agricultural monitoring are often deployed in outdoor environments in remote areas. Due to the exposure to harsh environments and the nature of deployment, sensors and other devices are susceptible to an increased rate of failure, which can take a system to unsafe and dangerous states. Failure of a smart agriculture system can cause significant harm to nature and people and reduce agricultural production. To address the concerns associated with the failure of the system, it is necessary to understand how the failures of the components of a system can contribute to causing the overall system failure. This paper adopts Fault Tree Analysis, a widely used framework for failure behaviour analysis in other safety-critical domains, to demonstrate the qualitative failure analysis of smart irrigation systems based on the components’ failure. / The full-text of this article will be released for public view at the end of the publisher embargo on 10 Dec 2024.

With increasing competitive pressures in today‟s market, it has become critical for businesses to recognise the significance of satisfying their customers so as to ensure their economic stability. Various studies have emphasised on the need for customer focus and project satisfaction in the construction industry sector. The industry, however, has not fully embraced the practice of project satisfaction, which is grounded on meeting the needs of the customer. Though most research on project satisfaction has focussed on the client, it is essential that the satisfaction of the project delivery team and in the wider context, the stakeholders be considered. In this case, the client is the centre of gravity of the project team. In order to satisfy the project team, there are challenges in assessing their requirements. This necessitates the need to develop a unique and robust method for capturing and analysing the level of integrated project team satisfaction. In this research, the project delivery team and the stakeholders have been lumped together as an integrated project team. Therefore, integrated project team satisfaction entails recognising the client and project participants‟ requirements that guarantees project successful completion and acceptance by the team. In view of this, this research presents a framework, which has been developed to plug these needs and challenges. The framework, known as the Satisfaction Assessment Integrated Framework (SAIF) involves an integrated approach that considers the participants of a construction project as a tree structure, and each member of that tree as an intermediate or top element. Relationships and interactions of the elements, and how these affect the overall satisfaction levels of a single project, are analysed based on understanding their requirements and invoking modern satisfaction attainment theory. The framework includes a method for understanding and identifying the satisfaction attributes; multi-attribute analysis for prioritising the satisfaction attributes of the clients and project participants; fault tree analysis strategy for defining the satisfaction relationship in a particular project team; and an assessment scoring system (a combination of multi-attribute analysis, and failure mode and effects analysis methodical approach) that evaluates how much each member of the project team meets the requirements or satisfaction attributes of other participants. Hence, SAIF, a novel assessment methodology, investigates and identifies possible links and the influence of integrating the construction project team and their satisfaction attributes with the aim of improving their satisfaction levels as a team. Through the findings of this research, recommendations are made to further explore the implications of satisfying a given participant against dissatisfying the participant; and subsequently improve the satisfaction assessment process.

根據研究報告調查發現，即使組織已經使用了安全機制仍無法完全阻止危害組織資訊安全事件的發生，這是因為組織的資訊安全管理是一個不斷改善的過程，並不是使用了安全防護措施之後，就可以高枕無憂，除了架構安全防護機制外，還需要去分析資訊的機密性、完整性或可得性等是否真能夠受到保護？所使用的安全機制是否真能解決組織的資訊安全問題？或是所提供的安全程度是否能接受等？ 為了解決上述等問題，本研究希望從管理的角度切入，應用錯誤樹分析方法在資訊安全管理的領域上，希望藉由此方法幫助管理者獲知組織的資訊安全需求，然後透過資訊安全管理不斷改善的過程，改善組織資訊安全的弱點，提高組織安全的可靠度。 依據研究架構，結合BS7799此資訊安全管理標準，並應用錯誤樹分析方法，將資訊安全政策轉換為資訊安全模型，由此資訊安全模型作進一步的定性與定量分析；本研究利用錯誤樹分析方法的六個步驟，實際模擬組織資訊安全需求獲得的過程，並透過分析的結果，幫助組織從中獲取資訊安全的需求，找出資訊安全的弱點，作為組織資訊安全改進的參考與依據。 / As the investigate report dictated, the degree of security of an information system does not only depend on the security mechanism installed by the organization. It is a continuous and recursive procedure. Most researches are technique-oriented currently. In order to adjust this bias, this research propose a new approach, which is from the management perspective. BS7799 is used for the information security policy reference. FTA is used to build up the information security model and acquire the requirements of an information system and verify its effectiveness. The result can promote the reliability of the information system and reduce the vulnerability of the system too.

Safety systems are designed to prevent the occurrence of certain conditions and their future development into a hazardous situation. The consequence of the failure of a safety system of a potentially hazardous industrial system or process varies from minor inconvenience and cost to personal injury, significant economic loss and death. To minimise the likelihood of a hazardous situation, safety systems must be designed to maximise their availability. Therefore, the purpose of this thesis is to propose an effective safety system design optimization scheme. A multi-objective genetic algorithm has been adopted, where the criteria catered for includes unavailability, cost, spurious trip and maintenance down time. Analyses of individual system designs are carried out using the latest advantages of the fault tree analysis technique and the binary decision diagram approach (BDD). The improved strength Pareto evolutionary approach (SPEA2) is chosen to perform the system optimization resulting in the final design specifications. The practicality of the developed approach is demonstrated initially through application to a High Integrity Protection System (HIPS) and subsequently to test scalability using the more complex Firewater Deluge System (FDS). Computer code has been developed to carry out the analysis. The results for both systems are compared to those using a single objective optimization approach (GASSOP) and exhaustive search. The overall conclusions show a number of benefits of the SPEA2 based technique application to the safety system design optimization. It is common for safety systems to feature dependency relationships between its components. To enable the use of the fault tree analysis technique and the BDD approach for such systems, the Markov method is incorporated into the optimization process. The main types of dependency which can exist between the safety system component failures are identified. The Markov model generation algorithms are suggested for each type of dependency. The modified optimization tool is tested on the HIPS and FDS. Results comparison shows the benefit of using the modified technique for safety system optimization. Finally the effectiveness and application to general safety systems is discussed.

Made available in DSpace on 2014-06-12T17:37:46Z (GMT). No. of bitstreams: 2 arquivo5337_1.pdf: 2712381 bytes, checksum: ef54386909f89cae6f4af5d76ab17550 (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2008 / Companhia Hidro Elétrica do São Francisco / Nos Sistemas Elétricos de Potência, os Compensadores Estáticos CE são equipamentos de elevada importância na regulação de tensão, tanto em regime permanente como em transitório, principalmente em sistemas onde os centros de carga estão localizados a grandes distâncias da geração. Esta dissertação, apresenta uma análise das causas de falha do Compensador Estático instalado na Subestação - SE de Fortaleza da Companhia Hidro Elétrica do São Francisco - CHESF, estado do Ceará, Brasil, com ênfase nas origens das falhas e em suas soluções, utilizando como ferramenta de análise a Árvore de Falhas deste Equipamento. Neste trabalho, encontramos a Árvore de Falhas do CE, composta por 62 eventos básicos, dos quais 20 apresentaram histórico suficiente para a análise paramétrica em um banco de dados de 22 anos. A partir das curvas de probabilidade de falha dos eventos básicos, elaborou-se um plano de ação com melhorias nos processos de manutenção, para viabilizar a elevação da disponibilidade do CE, com o objetivo de maximizar a remuneração da empresa Transmissora, no caso, a CHESF, e a confiabilidade do sistema de transmissão

Reliability based life cycle cost analysis is becoming an important consideration for decision-making in relation to bridge design, maintenance and rehabilitation. An optimal solution should ensure reliability during service life while minimizing the life cycle cost. Risk of failure is an important component in whole of life cycle cost for both new and existing structures. Research work presented here aimed to develop a methodology for evaluation of the risk of failure of reinforced concrete bridges to assist in decision making on rehabilitation. Methodology proposed here combines fault tree analysis and probabilistic time-dependent reliability analysis to achieve qualitative and quantitative assessment of the risk of failure. Various uncertainties are considered including the degradation of resistance due to initiation of a particular distress mechanism, increasing load effects, changes in resistance as a result of rehabilitation, environmental variables, material properties and model errors. It was shown that the proposed methodology has the ability to provide users two alternative approaches for qualitative or quantitative assessment of the risk of failure depending on availability of detailed data. This work will assist the managers of bridge infrastructures in making decisions in relation to optimization of rehabilitation options for aging bridges.

To improve safety, reliability, and efficiency of automotive vehicles and other technical applications, embedded systems commonly use fault diagnosis consisting of fault detection and isolation. Since many systems are constructed as distributed embedded systems including multiple control units, it is necessary to perform global fault isolation using for example a central unit. However, the drawbacks with such a centralized method are the need of a powerful diagnostic unit and the sensitivity against disconnections of this unit. Two alternative methods to centralized fault isolation are presented in this thesis. The first method performs global fault isolation by a istributed sequential computation. For a set of studied systems, themethod gives, compared to a centralizedmethod, amean reduction inmaximumprocessor load on any unitwith 40 and 70%for systems consisting of four and eight units respectively. The second method instead extends the result of the local fault isolation performed in each unit such that the results are globally correct. By only considering the components affecting each specific unit, the extended result in each agent is kept small. For a studied automotive vehicle, the second method gives, compared to a centralized method, a mean reduction in the sizes of the results and the maximum processor load on any unit with 85 and 90% respectively. To perform fault diagnosis, diagnostic tests are commonly used. If the additional evaluation of tests can not improve the fault isolation of a component then the component is ready. Since the evaluation of a test comes with a cost in for example computational resources, it is valuable to minimize the number of tests that have to be evaluated before readiness is achieved for all components. A strategy is presented that decides in which order to evaluate tests such that readiness is achieved with as few evaluations of tests as possible. Besides knowing how fault diagnosis is performed, it is also interesting to assess the effect that fault diagnosis has on for example safety. Since fault tree analysis often is used to evaluate safety, this thesis contributes with a systematic method that includes the effect of fault diagnosis in fault trees. The safety enhancement due to the use of fault diagnosis can thereby be analyzed and quantified.