Orientador: Carlos Amadeu Pallerosi / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-07-21T10:55:05Z (GMT). No. of bitstreams: 1 Dias_Acires_D.pdf: 44307682 bytes, checksum: 45a5e1e0305e0e8280a51c6b6bd10ebc (MD5) Previous issue date: 1996 / Resumo: Neste trabalho foi desenvolvida uma metodologia para análise da confiabilidade de freios pneumáticos automotivos com o objetivo de fornecer aos projetistas e analistas de sistemas de freios pneumáticos, ferramentas que facilitem a incorporação das variáveis confiabilísticas no projeto dos componentes, dos subsistemas e dos sistemas de freios, em tempo de projeto. Utilizou-se a distribuição probabilística de Weibull como a função representativa dos eventos de falha, calculando-se a confiabilidade, a não-confiabilidade, a taxa instantânea de falha e a função densidade de probabilidade de falha dos itens que compõem os circuitos de freio. O método de análise foi dividido em cinco etapas: modelo fisico, identificação dos itens do sistema, modelo confiabilístico, modelo matemático e modelo computacional. No modelo computacional foi desenvolvido o programa BRAKEREL (Brake Reliability Program), programado no Visual Basic for Windows, para calcular a confiabilidade, a não confiabilidade, a taxa instantânea de falha e a função densidade de probabilidade de falha para todos os itens do sistema, apresentando os resultados na forma de gráfico e de tabelas / Abstract: This work presents a methodology for reliability analysis of automotive pneumatic brakes, with the objective of providing the designers and the brake systems analysts with some tools which can facilitate the incorporation of the reliabilty variables in the design of the components, the subsystems and the brake systems, in project's realtime. The Weibull distribution is used as a function representing the failure events, calculating the reliability, the unreliability , hazard rate and failure density function, of the components of the brake circuits. The analysis method is composed of five steps: physical model, systems identification, reliabilitymodel, mathematical mode! and computational model. In the computational model it was developed the BRAKEREL program (Brake Reliability Program) using the Visual Basic for Windows in calculating the reliability, the unreliability, hazard rate and the failure density function, for alI the components of the system. The results are presented in grafical form and tables / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica

Orientadores: Christiano Lyra Filho, Celso Cavellucci / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-13T17:12:20Z (GMT). No. of bitstreams: 1 Bacalhau_EduardoTadeu_M.pdf: 2312425 bytes, checksum: c300ba31a847eef9ba5343cfd6548c0f (MD5) Previous issue date: 2009 / Resumo: O trabalho aborda a alocação ótima de recursos para manutenção de redes de distribuição de energia elétrica. O modelo matemático do problema procura representar os componentes das redes, suas inter-relações para operação das redes, suas contabilidades e mudanças de condições por ações de manutenções. O objetivo do processo de otimização é reduzir os custos de manutenção sob restrições de operação com determinados níveis de contabilidade, ao longo de um horizonte de planejamento. As melhores estratégias de manutenção podem ser obtidas através da solução de um problema de otimização combinatória inteiro misto, com variáveis discretas e contínuas. A principal contribuição do trabalho é o desenvolvimento de meta-heurísticas híbridas que possam encontrar estratégias de manutenções de melhor qualidade, considerando-se abordagens anteriores para o problema. São desenvolvidas três meta-heurísticas híbridas, que utilizam diferentes formas de articulações de Busca em Profundidade, Busca em Largura e Simulated Annealing. Estudos de casos realizam comparações entre as três abordagens e um algoritmo genético híbrido. A análise dos resultados permite destacar as qualidades de cada uma das abordagens. / Abstract: This work is concerned with the optimal allocation of maintenance resources on electric power distribution networks. The mathematical model represents the main components of the network, their interrelationships for the operation of the network, their reliabilities and the changes in condition due to maintenance procedures. The objective of the optimization process is the reduction of maintenance costs under constraints of reliability, during a given planning period. The best maintenance strategies can be obtained from the solution of a mixed integer combinatorial optimization problem, with continuous and discrete variables. The main contribution of the present work is the development hybrid heuristics that are able to obtain better solutions for the problem, with respect to previous approaches. Three hybrid heuristics are developed, based on the depth first, breath first and simulated annealing state space searches. Case studies compare the three approaches with a hybrid genetic algorithm previously proposed to address the problem. The analysis of results highlights the benefits of each approach. / Mestrado / Automação / Mestre em Engenharia Elétrica

Orientadores: Mario Jino, Adalberto Nobiato Crespo / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-25T04:04:06Z (GMT). No. of bitstreams: 1 Silva_OdairJacintoda_M.pdf: 2238493 bytes, checksum: 120710575da3bbe9052b22a2df5a3a07 (MD5) Previous issue date: 2014 / Resumo: Diversos estudos publicados indicam que a capacidade preditiva dos modelos de confiabilidade de software, que utilizam a informação da cobertura observada durante os testes, é melhor do que a capacidade preditiva dos modelos baseados no domínio do tempo. E, por isso, têm sido propostos por pesquisadores da área como uma alternativa aos modelos baseados no domínio do tempo. Entretanto, para chegar a uma conclusão sobre a superioridade desta classe de modelos é necessário avaliar a sua sensibilidade a variações do perfil operacional. Uma qualidade desejável dos modelos de confiabilidade de software é a de que sua capacidade preditiva não seja afetada por variações no perfil operacional de um software. Esta dissertação avalia, por meio de um experimento, o comportamento de dois modelos de confiabilidade de software que se baseiam na informação de cobertura do código: "Modelo Binomial Baseado em Cobertura" e "Modelo de Falhas Infinitas Baseado em Cobertura". O experimento aplica os modelos nos dados de falhas observados durante a execução de um programa em três perfis operacionais estatisticamente distintos. Adicionalmente, seis modelos de confiabilidade de software tradicionais são utilizados para estimar a confiabilidade do software utilizando os mesmos dados de falhas. Os modelos escolhidos foram: Musa-Okumoto, Musa Básico, Littlewood-Verral Linear, Littlewood-Verral Quadrático, Jelinski-Moranda e Geométrico. Os resultados mostram que a capacidade preditiva dos modelos "Modelo Binomial Baseado em Cobertura" e "Modelo de Falhas Infinitas Baseado em Cobertura" não é afetada com a variação do perfil operacional do software. O mesmo resultado não foi observado nos modelos de confiabilidade de software baseados no domínio do tempo, ou seja, a alteração do perfil operacional influencia a capacidade preditiva desses modelos. Um resultado observado, por exemplo, é de que nenhum dos modelos tradicionais pôde ser utilizado para estimar a confiabilidade do software aplicando os dados de falhas gerados por um dos perfis operacionais / Abstract: Several published studies indicate that the predictive ability of the software reliability models using test coverage information observed during the tests is better than the predictive ability of models based on time domain. And, therefore, have been proposed by researchers as an alternative to models based on time domain. However, to reach a conclusion about the superiority of this class of models is necessary to evaluate their sensitivity to variations in operational profile. A desirable quality of software reliability models is that their predictive ability is not affected by variations in the operational profile of a program. This dissertation analyzes by means of an experiment, the sensitivity of two software reliability models based on code coverage information: "Binomial Model Based on Coverage" and "Infinite Failure Model Based on Coverage". The experiment applies the models to data failures observed during the execution of a program according to three statistically distinct operational profiles. Additionally, six traditional software reliability models were used to estimate the reliability using the same software failure data. The models selected were: Musa-Okumoto, Musa Basic, Littlewood-Verrall Linear, Quadratic Littlewood-Verrall, Jelinski-Moranda and Geometric. The results show that the predictive ability of the models "Binomial Model Based on Coverage" and "Infinite Failure Model Based on Coverage" is not affected by varying the operational profile of the software. The same result was not observed in software reliability models based on time domain, i.e., changing the operational profile influences the predictive ability of these models. A result observed for example is that none of the traditional models could be used to estimate the software reliability using the fault data set generated by one of the operational profiles / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica

Orientador: José Maria Campos dos Santos / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-20T08:28:53Z (GMT). No. of bitstreams: 1 Machado_MarcelaRodrigues_M.pdf: 4137265 bytes, checksum: a1528ce4c60e2c600667f3691bb22fbf (MD5) Previous issue date: 2012 / Resumo: Esta trabalho, trata do estudo de quantificação de incertezas ou aleatoriedade existentes em sistemas mecânicos. Neste sentido, o método de expansão em Polinômio de Caos e a simulação de Monte Carlos são aplicados para obter a resposta de um problema com paramentos aleatórios. Além disso, estudos de confiabilidade em sistemas mecânicos também são abordados nesta dissertação. Com este propósito, os métodos de confiabilidade de primeira ordem e de segunda ordem são estudados e utilizados na análise de confiabilidade de sistemas mecânicos. Três problemas mecânicos diferentes foram abordados para os estudos mencionados. O primeiro aborda um problema dinâmico simples de um grau de liberdade, o segundo um problema de propagação de trinca em estrutura usando equação de Paris da mecânica da fratura linear e o terceiro um problema de detecção de falhas utilizando o método do elemento espectral em uma estrutura tipo viga. Para todos os casos parâmetros incertos foram considerados. Portanto, este trabalho contribui para o estudo da quantificação de incertezas em problemas de engenharia, bem como a confiabilidade de sistemas mecânicos levando em consideração as possíveis aleatoriedades presentes neles. Os casos simulados são realizados com o objetivo de verificar a validade do modelo incluindo os efeitos das incertezas dos parâmetros e avaliar sua eficiência computacional / Abstract: This work, deals with the study of uncertainty quantification or mechanical systems randomness. In this sense, the polynomial chaos expansion method and Monte Carlo simulation are applied to obtain the response of a problem with random parameters. In addition, reliability studies on mechanical systems are also discussed in this dissertation. For this purpose, the fist- and second-order reliability methods are studied and used for the analysis of mechanical system reliability. Three different mechanical problems have been addressed in the studies mentioned. The first approach is a simple one degree of freedom dynamic problem, the second is a crack propagation problem based on Paris' linear fracture mechanics equation and the third is a damage detection problem using the spectral element method using, a beam type structure. For all cases uncertain parameters were considered. Therefore, this work contributes to the study of uncertainty quantification in engineering problems, as well as the reliability of mechanical systems taking into account the possible randomness present in them. The simulated cases are performed with the objective of verifying the validity of the model including the effects of uncertainties in parameters and to assess its computational efficiency / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

Reliability as an engineering discipline has grown in importance in systems development and manufacturing since its inception in the 1950s. This growth in importance is driven by several factors, including increasing complexity and sophistication of systems, public awareness of and insistence on product quality and availability, new laws and regulations concerning product liability, government contractual requirements to meet reliability and maintainability performance specifications, and profit considerations resulting from the high cost of failures. Such failures lead to increased costs for warranty programs, increased rate of repairs, and loss of sales because of decreased customer satisfaction. Reliability engineering is the discipline of ensuring that a product or system will work properly during a specified period of time. Therefore, the aim of reliability engineering is to delay the failures and then to maximize the life of the product. Studying the reliability of renewable energy systems in particular became more important in the last decade because of the need to find long life reliable substitutions to fossil fuels. One of these systems that recently has gained increasing interest because of research and development in the field of sustainable solar energy systems is Concentrated PhotoVoltaic (CPV) systems. These advancements could enable: 1) Higher conversion efficiencies, 2) Lower capital costs, and 3) Better reliability than competing products. The CPV system architecture creates the potential for higher conversion efficiencies as contrasted with other sustainable solar energy systems such as flat plate PhotoVoltaic (PV) system. Because CPV systems require significantly less silicon than other sustainable solar energy systems, their resulting lower capital costs was viewed as the technology’s major potential advantage over flat-plate PV, particularly for utility-scale applications. That argument has become less relevant with the dramatic reduction in silicon prices over the last several years. Increasing the reliability of the CPV systems could potentially significantly decrease the cost of electricity produced by these systems. If so, this could have a great influence on the economy and the cost of life especially in areas that have substantial amount of solar radiation like Arizona in the United States. Therefore, the present research explores various extent reliability methods, synthesizes a new method, and applies that method to a specific CPV design. The results show that applying this method to the design of the considered system should result in a significant improvement in CPV system reliability. Finally, the present research considers the opportunities for extending this work on different types of systems including software systems.

M.Phil. / The implementation of a maintenance strategy without taking the uniqueness of the specific business into account, will not necessarily result in a high level of performance. The maintenance function should be developed specifically to support the particular business processes and technology in use. There is presently a large gap between the results obtained through the implementation of the maintenance strategy at a major coal-mining complex and the desired targets to be met. To close the gap, this dissertation suggests that support systems should be implemented to sustain growth and stability. The dissertation specifically proposes the creation of a Central Support Function to support the maintenance strategy, which has been implemented together with the Enterprise Management System (EMS) with the System Application Product (SAP) as an enabler.

Production Line Systems (PLS) are ubiquitous in today’s manufacturing industry. The need for enhanced efficiencies and higher throughput in such systems has increased their complexity and size that has made performance analysis challenging for practitioners. This thesis introduces a novel approach based on Product Service System (PSS) design and analysis which simplifies Production Line System study and identifies opportunities for performance improvement that can be quantified based on the hardware and maintenance system performance. The approach involves modelling and simulation techniques based on reliability engineering principles and systems thinking. In order to apply the principles of PSS approach to PLS, it is essential to draw a comparison between PLS and PSS, so as to take account of the differences while applying the new approach; a literature review has been carried out on PSS Design and Analysis, that identified the state of the art modelling and simulation techniques in PSS. Additionally, a separate literature review on maintenance system and production line was carried out. This enabled the PSS methodology to be applied to PLS by incorporating the differences. A systems thinking approach has been employed to create the static simulation model of the integrated production line system by means of schematic representations. Key improvement areas, identified from the static simulation model have been modelled dynamically to incorporate the stochastic behaviour of the system. All the dynamic models are developed using a Discrete Event Simulation platform. These models were supported by Monte Carlo Simulation, queuing principles, probabilistical and statistical methods pertinent to reliability engineering. The novel integrated simulation model consists of a production line model and a maintenance system model. The production line model simulates two types of failures in addition to the outages in the system: breakdowns and short stops. The maintenance system model simulates the maintenance actions in the production line by considering the resources availability, repair time, and resources travelling time amongst others. In addition, the maintenance model is capable of optimizing the preventive maintenance interval for maintainable failures for cost, availability and criticality while taking into account the maintenance effectiveness value from the failure data. The simulation model is validated using an industrial case study which consists of a large production line for beer. Sensitivity studies on the simulation model enabled the case study company to focus on strategies for throughput improvement by improving the reliability and maintainability, optimal resources allocation and maintenance interval optimization in targeted areas in the large and complex system. The model developed is generic and can easily be applied to analyse other industrial production line systems. It can also be used as a design tool for new production lines.

As electronic packages and their thermal solutions become more complex the reliability margins in the thermal solutions diminish and become less tolerant to errors in reliability predictions. The current method of thermally stress testing thermal solutions can be over or under predicting end of life thermal performance. Benefits of accurate testing and modeling are improved silicon yield in manufacturing, improved performance, lower cost thermal solutions, and shortened test times. The current method of thermally stress testing is to place the entire unit in an elevated isothermal temperature and periodically measure thermal performance. Isothermally aging is not an accurate representation of how the unit will be used by the customer and does not capture the thermal gradients and mechanical stresses due to different coefficients of thermal expansion of the materials used in the thermal solution. A new testing system, CITRAM which is an acronym for Constant Interface Temperature Reliability Method, has been developed that uses an electronic test board. The approach captures the thermal and mechanical stresses accurately and improves test time by 20-30% as a result of automation. Through this study a difference in the two methods has been identified and the new CITRAM method should be adopted as current practice.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaf 113. / by Bak Kong Low. / M.S.

Uncertainties in engineering design exist due to the random nature of loads and materials, lack of knowledge, and imperfect modelling of design parameters. Conventional design methods based on deterministic procedures do not always yield designs having consistent safety. In recent years considerable research has been conducted in the use of probability theory for modelling uncertainties in engineering designs and several probabilistic design formats have been developed. Probability based design methods provide a unified procedure applicable to all construction materials, all loads, and all types of uncertainties. Code committees are currently working on the development of the new design codes for various construction materials such as steel, concrete, and wood based on probabilistic concepts. The objective of this study is to study a probability based design format for wood members. Reliability analysis of wood structural elements such as beams, columns, and beam-columns is conducted, and the risk level is measured by the reliability or safety index, β. Wood members subjected to dead plus live load and dead plus snow load combinations are considered. After conducting a reliability analysis of current designs, a target reliability index is selected. The reliability index is then used in conjunction with the predetermined load factors and load combinations to determine resistance factors. Finally, a design format is proposed for Load and Resistance Factor Design for wood structures. / M.S.