L'homme reste l'un des éléments essentiels des opérations de transport modernes. Les méthodes d'analyse de la fiabilité humaine (HRA) fournissent une approche multidisciplinaire pour évaluer l'interaction entre les humains et le système. Cette thèse propose une nouvelle méthodologie HRA appelée PRELUDE (Performance shaping factor based human REliability assessment using vaLUation-baseD systems). Les facteurs de performance sont utilisés pour caractériser un contexte opérationnel dangereux. Le cadre de la théorie des fonctions de croyance et des systèmes d'évaluation (VBS) utilise des règles mathématiques pour formaliser l'utilisation de données d'experts et la construction d'un modèle de fiabilité humaine, il est capable de représenter toutes sortes d'incertitudes. Pour prédire la probabilité d'erreur humaine dans un contexte donné, et de fournir une remontée formelle pour réduire cette probabilité. La deuxième partie de ce travail démontre la faisabilité de PRELUDE avec des données empiriques. Un protocole pour obtenir des données à partir de simulateurs, et une méthode de transformation et d'analyse des données sont présentés. Une campagne expérimentale sur simulateur est menée pour illustrer la proposition. Ainsi, PRELUDE est en mesure d'intégrer des données provenant de sources (empiriques et expertes) et de types (objectifs et subjectifs) différents. Cette thèse aborde donc le problème de l'analyse des erreurs humaines, en tenant compte de l'évolution du domaine des méthodes HRA. Elle garde la facilité d'utilisation de l'industrie ferroviaire, fournissant des résultats qui peuvent facilement être intégrés avec les analyses de risques traditionnelles. Dans un monde de plus en plus complexe et exigeant, PRELUDE fournira aux opérateurs ferroviaires et aux autorités réglementaires une méthode permettant de s'assurer que le risque lié à l'interaction humaine est compris et géré de manière appropriée dans son contexte. / Humans are and remain one of the critical constituents of modern transport operations. Human Reliability Analysis (HRA) methods provide a multi-disciplinary approach: systems engineering and cognitive science methods to evaluate the interaction between humans and the system. This thesis proposes a novel HRA methodology acronymed PRELUDE (Performance shaping factor based human REliability assessment using vaLUation-baseD systEms). Performance shaping factors (PSFs) are used to characterize a dangerous operational context. The proposed framework of Valuation-based System (VBS) and belief functions theory (BFT) uses mathematical rules to formalize the use of expert data and construction of a human reliability model capable of representing all kinds of uncertainty. PRELUDE is able to predict the human error probability given a context, and also provide a formal feedback to reduce the said probability. The second part of this work demonstrates the feasibility of PRELUDE with empirical data from simulators. A protocol to obtain data, a transformation and data analysis method is presented. An experimental simulator campaign is carried out to illustrate the proposition. Thus, PRELUDE is able to integrate data from multiple sources (empirical and expert) and types (objective and subjective). This thesis, hence address the problem of human error analysis, taking into account the evolution of the HRA domain over the years by proposing a novel HRA methodology. It also keeps the rail industry’s usability in mind, providing a quantitative results which can easily be integrated with traditional risk analyses. In an increasingly complex and demanding world, PRELUDE will provide rail operators and regulatory authorities a method to ensure human interaction-related risk is understood and managed appropriately in its context.

A APS (Análise Probabilística de Segurança) de instalações industriais é assunto que evoluiu com a complexidade dos sistemas. A princípio, foram desenvolvidas ferramentas e técnicas com o propósito de analisar plantas já instaladas, possibilitando a identificação de fenômenos e mecanismos de falha desconhecidos até então. Com a evolução dos estudos dos acidentes, foram desenvolvidas técnicas aplicáveis às fases pré-operacionais com o propósito de diminuir os riscos na operação. Observa-se, portanto, um bom número de técnicas ideais para analisar projetos prontos ou em fase de conclusão. O mesmo não é observado para a fase de concepção. Apesar disto, cada vez mais especialistas na área de risco propõem que as considerações de segurança são mais eficazes quando ponderadas ao longo de toda a vida dos sistemas críticos. O estudo das APS realizadas no mundo em várias indústrias ajuda a entender o consenso sobre a contribuição potencial destas análises no desenvolvimento de novos sistemas. Para explorar este potencial, é essencial a elaboração de processos e modelos prospectivos que sejam simples, quantitativos, realistas, capazes de alimentar análises no estágio de projeto e que tragam resultados que possam ser interpretados pelos profissionais envolvidos no processo decisório. Estas considerações são extensíveis à ACH (Análise de Confiabilidade Humana), i.e., poucas são as ferramentas que ponderam aspectos operacionais, em especial o desempenho humano, na fase de projeto. A reconhecida contribuição do fator humano em acidentes envolvendo sistemas complexos - por vezes atribuída à falta de ferramentas adequadas para sua consideração na fase de projeto - evidencia ainda mais esta lacuna. Neste contexto, esta tese apresenta o desenvolvimento de uma metodologia e de uma técnica para a consideração precoce da confiabilidade humana na concepção de sistemas complexos, sendo que: 1) o desenvolvimento desta metodologia primou pela facilidade de entendimento de suas etapas e resultados, i.e., procurou-se a inteligibilidade para as pessoas envolvidas no projeto, sendo especialistas em ACH ou não, e; 2) a TECHR (Technique for Early Consideration of Human Reliability) foi concebida com o propósito de desenvolver um modelo prospectivo para o desempenho humano que possa ser explorado na fase de concepção de sistemas, e se baseia no aproveitamento da opinião de especialistas em relação a sistemas que operam ou operaram nos últimos anos para obter estimativas das probabilidades dos diversos tipos de erro humano que podem ocorrer durante a execução de uma ação específica. A metodologia proposta e a TECHR resultam em um procedimento simples e capaz de produzir modelos extremamente úteis na fase de projeto, representando uma contribuição original para o estado da arte da concepção de sistemas baseada em dados incertos. / PSA (Probabilistic Safety Assessment) is an industrial plant issue that has evolved with the complexity of systems. Initially, tools and techniques have been developed with the main purpose of analyzing operational plants, enabling the identification of phenomena and fault mechanisms hitherto not highlighted. With the evolution of accidents studies, some techniques applicable to pre-operational phases were developed in order to reduce the risks in operation. Therefore, a number of techniques adequate to analyze ready or near completion designs can be found. The same is not observed for the early design phase. Despite this, more and more experts in the risk assessment field suggest that safety considerations are most effective when assessed over the whole life of critical systems. Probabilistic safety analyses performed worldwide in various industries help us understand the consensus on the potential contribution of these analyses for developing new systems. To exploit this potential, it is essential to develop processes and prospective models that are simple, quantitative, realistic, able to feed analyses at the design stage and to bring results that can be interpreted by the professionals involved in the decision making process. These considerations are extended to HRA (Human Reliability Analysis), i.e., there are few tools that consider operational aspects, especially human performance, during the design phase. The recognized contribution of the human factor in accidents involving complex systems - sometimes attributed to the lack of suitable tools for its consideration in the design phase - further highlights this gap. In this context, this thesis presents a methodology and a technique developed for the early consideration of human reliability in complex systems design, and: 1) the development of this methodology has prioritized the easy understanding of its steps and results, i.e., its intelligibility for people involved in the system design has been sought, with expertise in HRA or not, and; 2) the technique for early consideration of human reliability (TECHR) was designed for developing a prospective human performance model that can be exploited in the system design phase, and is based on the use of expert opinion in relation to systems that operate or have operated in recent years to obtain estimates of the probabilities of the various types of human error that may occur during the performance of a specific action. The proposed methodology and technique result in a simple procedure capable of producing useful models for the design phase, representing an original contribution to the state of the art of systems conception under uncertainty.

Grades serve as one of the primary indicators of student learning, directing subsequent actions for students, instructors, and administrators, alike. Therefore, grade validity—that is, the extent to which grades communicate a meaningful and credible representation of what they purport to measure—is of utmost importance. However, a grade cannot be valid if one cannot trust that it will consistently and reliably result in the same value, regardless of who makes a measure or when they make it. Unfortunately, such reliability becomes increasingly challenging to achieve with larger class sizes, especially when utilizing multiple evaluators, as is often the case with mandatory introductory courses at large universities. Reliability suffers further when evaluating open-ended tasks, as are prevalent in authentic, high-quality engineering coursework.<div><br></div><div>This study explores grading reliability in the context of a large, multi-section engineering course. Recognizing the number of people involved and the plethora of activities that affect grading outcomes, the study adopts a systems approach to conduct a human reliability analysis using the Functional Resonance Analysis Method. Through this method, a collection of data sources, including course materials and observational interviews with undergraduate teaching assistant graders, are synthesized to produce a general model for how actions vary and affect subsequent actions within the system under study. Using a course assignment and student responses, the model shows how differences in contextual variables affect expected actions within the system. Next, the model is applied to each of the observational interviews with undergraduate teaching assistants to demonstrate how these actions occur in practice and to compare graders to one another and with expected behaviors. These results are further related to the agreement in system outcomes, or grades, assigned by each grader to guide analysis of how actions within the system affect its outcome.<br></div><div><br></div><div>The results of this study connect and elaborate upon previous models of grader cognition by analyzing the phenomenon in engineering, a previously unexplored context. The model presented can be easily generalized and adapted to smaller systems with fewer actors to understand sources of variability and potential threats to outcome reliability. The analysis of observed outcome instantiations guides a set of recommendations for minimizing grading variability.<br></div>

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Submitted by Daniella Sodre (daniella.sodre@ufpe.br) on 2015-04-10T16:37:01Z No. of bitstreams: 2 TESE Rômulo Fernando Teixeira Vilela.pdf: 3159637 bytes, checksum: d8b68b1fd93d79fe6162c4abdd0b1aa0 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) / Made available in DSpace on 2015-04-10T16:37:01Z (GMT). No. of bitstreams: 2 TESE Rômulo Fernando Teixeira Vilela.pdf: 3159637 bytes, checksum: d8b68b1fd93d79fe6162c4abdd0b1aa0 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2013-02-27 / Com os avanços em hardware, a engenharia de confiabilidade nos últimos 30 anos, tem nos mostrado equipamentos e sistemas complexos com níveis de falha muito baixos. Sistemas complexos na indústria nuclear, aeroespacial, química, elétrica entre outras possuem hoje em dia equipamentos e sistemas com níveis de confiabilidade que tem atendido adequadamente a sociedade. Entretanto, a operação e manutenção destes sistemas não dependem exclusivamente do desempenho intrínseco dos correspondentes equipamentos, dependem também da ação humana. Grandes acidentes no passado recente como Chernobyl, Bhopal, da nave Challenger e os grandes apagões no Brasil, colocaram em evidência a necessidade de redução do erro humano em sistemas complexos. A análise da confiabilidade humana surge assim como um apoio para a análise destes sistemas de operação e manutenção. Desde a década de 80 alguns avanços foram surgindo no estudo da confiabilidade humana. Técnicas como THERP, ATHEANA, CREAM e IDAC, se consolidaram ao longo do tempo como boas aplicações práticas para estudar, medir e prever o erro humano. Porém os fatores de desempenho utilizados em quase todas as técnicas supracitadas, tem se mostrado difíceis de serem estimados de um ponto de vista particular. Além disso, as particularidades do setor Hidroelétrico de Potência, definidas nos Procedimentos de Rede do Operador Nacional do Sistema (ONS) e nos instrumentos normativos da Agencia Reguladora ANEEL têm levado a necessidade de uma taxonomia que possa se adaptar a este importante e estratégico setor. Nesta tese, é proposta uma taxonomia e um modelo da sequência do processo de erro, para avaliação deste erro humano especificamente concebido para atender ao contexto de operação e manutencão do Sistema Hidroelétrico de Potência. Para ilustrar a nova taxonomia, foram coletados e analisados dados de cerca de dez anos de registro de erro humano de uma empresa de geração e transmissão de energia elétrica brasileira. Foram coletados 605 relatórios de desligamento por erro humano desde 1998 até 2009. Uma metodologia BBN-Base para a quantificação do erro humano é também discutida. A taxonomia e o modelo da sequência do processo de erro humano tanto quanto o modelo BBN-Based são ilustrados via um exemplo de uma aplicação no contexto de uma indústria Brasileira Hidroelétrica de Potência.-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------With advances in hardware reliability engineering in the last 30 years, we have seen equipment and complex systems with very low levels of failure. Complex systems in the nuclear industry, aerospatiale sector, chemical industries, electrical industries and others now have equipment and systems with levels of reliability that has adequately served the society. However, the operation and maintenance of these systems do not rely solely on intrinsec performance of the corresponding equipment, but they also depend on human action. Major accidents in the recent past such Chernobyl, Bhopal, the Challenger shuttle and major recent power blackouts in Brazil, highlighted the need to reduce human error in complex systems. The human reliability assessment emerges as a support to the analisys of the operation and maintenance of these type of systems. Since the late 80th some advances have emerged in the study of human reliability. Techniques such as THERP, ATHEANA, CREAM and IDAC, have been consolidated over time for the study, measure and prediction of human error. However performance shaped factors used in almost all the aforementioned techniques have proven difficult to be estimated from a practical standpoint. In addition, the specifics of the Hydroelectric Power Industry defined in the Grid Procedures of the National System Operator (Operador Nacional so Sistema, ONS) and the regulatory instruments of ANEEL (Agencia Nacional de Energia Eletrica) Regulatory Agency have led to the necessity of a taxonomy that can adapt for this important strategic sector. In this thesis, it is proposed a taxonomy and model of error sequence process for assessment of human error specifically designed to meet the context of operation and maintenance of Hydroelectric Power System. To illustrate the new taxonomy it was collected and analyzed data from about ten years of human error records related to the generation and transmission of Hydroelectric Power Company in Brazil. It was collected 605 reports by human error shutdown from 1998 to 2009. A BBN-Base methodology for the quantification of human error is also discusses. The taxonomy, model for error sequence process as well as the BBN-Based model are illustrated via an example of application in the context of the Brazilian Hydroelectric Power Industry.