Made available in DSpace on 2014-10-09T12:48:53Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:01:14Z (GMT). No. of bitstreams: 1 09627.pdf: 6224254 bytes, checksum: 0192b8abd2aed7811607e803516e20a7 (MD5) / Dissertacao (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP

Submitted by Claudinei Pracidelli (cpracide@ipen.br) on 2016-02-03T11:55:07Z No. of bitstreams: 0 / Made available in DSpace on 2016-02-03T11:55:07Z (GMT). No. of bitstreams: 0 / O trabalho busca o desenvolvimento de um método experimental implementado em um software Web voltado à tomada de decisão, abordando mais especificadamente os processos de levantamento de ideias e geração de alternativas. Referências teóricas foram utilizadas para subsidiar os elementos, processos e tecnologias do software frente à áreas de tomada de decisão e sistemas colaborativos. As principais ferramentas disponíveis foram analisadas sob o contexto de tecnologias abertas, tendo algumas características de resolução de problemas observadas. A proposta combina elementos do brainstorming em seu formato eletrônico e do método de apresentação de dados da tabela de estratégias, com referência nas funcionalidades de sistemas amplamente utilizados e que operam sobre a priorização das informações por pequenos grupos de usuários. Fundamentações teóricas foram desenvolvidas e funcionalidades chave destes sistemas voltados à resolução de problemas foram analisadas. Para fins de demonstração, um caso prático foi realizado no Instituto de Pesquisas Energéticas e Nucleares, com ganhos e limitações encontradas no processo do software e da prática empregada. com a finalidade de apresentar os ganhos e limitações encontradas com o uso da ferramenta. / Dissertação (Mestrado em Tecnologia Nuclear) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

This work was undertaken as a final year project in Computer Engineering, within the Department of Computer and Information Science at Linköping University. At the Department of Computer and Information Science, work oriented at testing and analyzing applications is developed to provide solution approaches to problems that arise in system product development. One of the current applications being developed is the ‘Systemics Analyst’. The purpose of the application is to facilitate for system developers with an analysis tool permitting insights on system reliability, system critical components, how to improve the system and the consequences as well as risks of a system failure. The purpose of the present thesis was to enhance the ‘Systemics Analyst application’ by incorporating an ‘automated model-based reliability prediction’ and ‘fault tree analysis’ modules. This enables reliability prediction and fault tree analysis diagrams to be generated automatically from the data files and relieves the system developer from manual creation of the diagrams. The enhanced Systemics Analyst application managed to present the results in respective models using the new incorporated functionality. To accomplish the above tasks, ‘Systemics Analyst application’ was integrated with a library that handles automated model-based reliability prediction and fault tree analysis, which is described in this thesis. The reader will be guided through the steps that are performed to accomplish the tasks with illustrating figures, methods and code examples in order to provide a closer vision of the work performed.

The growing application of risk analysis in dam safety, especially for the owners of large numbers of dams (e.g., U.S. Army Corps of Engineers), has motivated the development of a new tool (DAMRAE) for event tree based dam safety risk analysis. Various theoretical challenges were overcome in formulating the computational framework of DAMRAE and several new computational concepts were introduced. The concepts of Connectivity and Pedigree matrices are proposed to quantify the user-drawn event tree structures with proper accounting of interdependencies among the event tree branches. A generic calculation of Common-Cause Adjustment for the non-mutually exclusive failure modes is implemented along with introducing the new concepts of system response probability and consequence freezing. New output presentation formats such as cumulative risk estimate vs. initiating variable plots to analyze the increase of an incremental (annualized) risk estimate as a function of initiating variable are introduced. An additional consideration is given to the non-breach risk estimates in the risk modeling and new output formats such as non-breach F-N and F-$ charts are included as risk analysis outputs. DAMRAE, a Visual Basic.NET based framework, provides a convenient platform to structure the risk assessment of a dam in its existing state and for alternatives or various stages of implementing a risk reduction plan. The second chapter of the dissertation presents the architectural framework of DAMRAE and describes the underlying theoretical and computational logic employed in the software. An example risk assessment is presented in the third chapter to demonstrate the DAMRAE functionalities. In the fourth chapter, the DAMRAE framework is extended into DAMRAE-U to incorporate uncertainty analysis functionality. Various aspects and requirements reviewed for uncertainty analysis in the context of dam safety risk assessment and theoretical challenges overcome to develop the computational framework for DAMRAE-U are described in this chapter. The capabilities of DAMRAE-U are illustrated in the fifth chapter, which contains an example dam safety risk assessment with uncertainty analysis. The dissertation concludes with a summary of DAMRAE features and recommendations for further work in the sixth chapter.

No description available.

Low volume high value (LVHV) supply chains such as airline manufacturing, power plant construction, and shipbuilding are especially susceptible to risks. These industries are characterized by long lead times and a limited number of suppliers that have both the technical know-how and manufacturing capabilities to deliver the requisite goods and services. Disruptions within the supply chain are common and can cause significant and costly delays. Although supply chain risk management and supply chain reliability are topics that have been studied extensively, most research in these areas focus on high vol- ume supply chains and few studies proactively identify risks. In this research, we develop methodologies to proactively and quantitatively identify and mitigate supply chain risks within LVHV supply chains. First, we propose a framework to model the supply chain system using fault-tree analysis based on the bill of material of the product being sourced. Next, we put forward a set of mathematical optimization models to proactively identify, mitigate, and resource at-risk suppliers in a LVHV supply chain with consideration for a firm’s budgetary constraints. Lastly, we propose a machine learning methodology to quan- tify the risk of an individual procurement using multiple logistic regression and industry available data, which can be used as the primary input to the fault tree when analyzing overall supply chain system risk. Altogether, the novel approaches proposed within this dissertation provide a set of tools for industry practitioners to predict supply chain risks, optimally choose which risks to mitigate, and make better informed decisions with respect to supplier selection and risk mitigation while avoiding costly delays due to disruptions in LVHV supply chains.

Yes / Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) have made the reliability analysis process less expensive in terms of effort and time required. HiP-HOPS uses an analytical modelling approach for Fault tree analysis to automate the reliability analysis process, where each system component is associated with its failure rate or failure probability. However, such non-state-space analysis models are not capable of modelling more complex failure behaviour of component like failure/repair dependencies, e.g., spares, shared repair, imperfect coverage, etc. State-space based paradigms like Markov chain can model complex failure behaviour, but their use can lead to state-space explosion, thus undermining the overall analysis capacity. Therefore, to maintain the benefits of MBSA while not compromising on modelling capability, in this paper, we propose a conceptual framework to incorporate complex basic events in HiP-HOPS. The idea is demonstrated via an illustrative example. / DEIS H2020 Project under Grant 732242.

Yes / Over the years, several approaches have been developed for the quantitative analysis of dynamic fault trees (DFTs). These approaches have strong theoretical and mathematical foundations; however, they appear to suffer from the state-space explosion and high computational requirements, compromising their efficacy. Modularisation techniques have been developed to address these issues by identifying and quantifying static and dynamic modules of the fault tree separately by using binary decision diagrams and Markov models. Although these approaches appear effective in reducing computational effort and avoiding state-space explosion, the reliance of the Markov chain on exponentially distributed data of system components can limit their widespread industrial applications. In this paper, we propose a hybrid modularisation scheme where independent sub-trees of a DFT are identified and quantified in a hierarchical order. A hybrid framework with the combination of algebraic solution, Petri Nets, and Monte Carlo simulation is used to increase the efficiency of the solution. The proposed approach uses the advantages of each existing approach in the right place (independent module). We have experimented the proposed approach on five independent hypothetical and industrial examples in which the experiments show the capabilities of the proposed approach facing repeated basic events and non-exponential failure distributions. The proposed approach could provide an approximate solution to DFTs without unacceptable loss of accuracy. Moreover, the use of modularised or hierarchical Petri nets makes this approach more generally applicable by allowing quantitative evaluation of DFTs with a wide range of failure rate distributions for basic events of the tree. / This work was supported in part by the Dependability Engineering Innovation for Cyber Physical Systems (CPS) (DEIS) H2020 Project under Grant 732242, and in part by the LIVEBIO: Light-weight Verification for Synthetic Biology Project under Grant EPSRC EP/R043787/1.

Yes / Risk assessment methods have been widely used in various industries, and they play a significant role in improving the safety performance of systems. However, the outcomes of risk assessment approaches are subject to uncertainty and ambiguity due to the complexity and variability of system behaviour, scarcity of quantitative data about different system parameters, and human involvement in the analysis, operation, and decision-making processes. The implications for improving system safety are slowly being recognised; however, research on uncertainty handling during both qualitative and quantitative risk assessment procedures is a growing field. This paper presents a review of the state of the art in this field, focusing on uncertainty handling in fault tree analysis (FTA) based risk assessment. Theoretical contributions, aleatory uncertainty, epistemic uncertainty, and integration of both epistemic and aleatory uncertainty handling in the scientific and technical literature are carefully reviewed. The emphasis is on highlighting how assessors can handle uncertainty based on the available evidence as an input to FTA.

No / Reliability evaluation for ensuring the uninterrupted system operation is an integral part of dependable system development. Model-based safety analysis (MBSA) techniques such as Hierarchically Performed Hazard Origin and Propagation Studies (HiP-HOPS) have made the reliability analysis process less expensive in terms of effort and time required. HiP-HOPS uses an analytical modelling approach for Fault tree analysis to automate the reliability analysis process, where each system component is associated with its failure rate or failure probability. However, such non-state-space analysis models are not capable of modelling more complex failure behaviour of component like failure/repair dependencies, e.g., spares, shared repair, imperfect coverage, etc. State-space based paradigms like Markov chain can model complex failure behaviour, but their use can lead to state-space explosion, thus undermining the overall analysis capacity. Therefore, to maintain the benefits of MBSA while not compromising on modelling capability, in this paper, we propose a conceptual framework to incorporate complex basic events in HiP-HOPS. The idea is demonstrated via an illustrative example. / This conference paper is available to view at http://hdl.handle.net/10454/17423.