962 resultados para Process monitoring


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The success of manufacturing composite parts by liquid composite molding processes with RTM depends on tool designs, efficient heat system, a controlled injection pressure, a stabilized vacuum system, besides of a suitable study of the preform lay-up and the resin system choice. This paper reports how to assemble a RTM system in a laboratory scale by specifying heat, injection and vacuum system. The design and mold material were outlined by pointing out its advantages and disadvantages. Four different carbon fiber fabrics were used for testing the RTM system. The injection pressure was analyzed regarding fiber volume content, preform compression and permeability, showing how these factors can affect the process parameters. The glass transition temperature (Tg) around 203 ºC matched with the aimed temperature of the mold which ensured good distribution of the heat throughout the upper and lower mold length. The void volume fraction in a range of 2% confirmed the appropriate RTM system and parameters choice.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper presents a multi-agent architecture that was designed to develop processes supervision and control systems, with the main objective to automate tasks that are repetitive and stressful, and error prone when performed by humans. A set of agents were identified, based on the study of a number of applications found in the literature, that use the approach of multi-agent systems for data integration and process monitoring to faults detection and diagnosis, these agents are used as basis of the proposed multi-agent architecture. A prototype system for the analysis of abnormalities during oil wells drilling was developed.

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Beim Laser-Sintern wird das Pulverbett durch Heizstrahler vorgeheizt, um an der Pulveroberfläche eine Temperatur knapp unterhalb des Materialschmelzpunktes zu erzielen. Dabei soll die Temperaturverteilung auf der Oberfläche möglichst homogen sein, um gleiche Bauteileigenschaften im gesamten Bauraum zu erzielen und den Bauteilverzug gering zu halten. Erfahrungen zeigen jedoch sehr inhomogene Temperaturverteilungen, weshalb oftmals die Integration von neuen oder optimierten Prozessüberwachungssystemen in die Anlagen gefordert wird. Ein potentiell einsetzbares System sind Thermographiekameras, welche die flächige Aufnahme von Oberflächentemperaturen und somit Aussagen über die Temperaturen an der Pulverbettoberfläche erlauben. Dadurch lassen sich kalte Bereiche auf der Oberfläche identifizieren und bei der Prozessvorbereitung berücksichtigen. Gleichzeitig ermöglicht die Thermografie eine Beobachtung der Temperaturen beim Lasereingriff und somit das Ableiten von Zusammenhängen zwischen Prozessparametern und Schmelzetemperaturen. Im Rahmen der durchgeführten Untersuchungen wurde ein IR-Kamerasystem erfolgreich als Festeinbau in eine Laser-Sinteranlage integriert und Lösungen für die hierbei auftretenden Probleme erarbeitet. Anschließend wurden Untersuchungen zur Temperaturverteilung auf der Pulverbettoberfläche sowie zu den Einflussfaktoren auf deren Homogenität durchgeführt. In weiteren Untersuchungen wurden die Schmelzetemperaturen in Abhängigkeit verschiedener Prozessparameter ermittelt. Auf Basis dieser Messergebnisse wurden Aussagen über erforderliche Optimierungen getroffen und die Nutzbarkeit der Thermografie beim Laser-Sintern zur Prozessüberwachung, -regelung sowie zur Anlagenwartung als erster Zwischenstand der Untersuchungen bewertet.

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Para que a sustentabilidade seja gerenciada e praticada de maneira efetiva, ela deve ser mensurada, utilizando-se de métodos de avaliação da sustentabilidade. Estão disponíveis diferentes métodos de avaliação, que geralmente reduzem o resultado desse levantamento à indicadores de desempenho ambiental, econômico e social (POPEA; ANNANDALE; MORISON-SAUNDERSB, 2004). Uma das denominações mais bem aceitas e difundidas para a conjunção da dimensão ambiental e econômica é conhecida por avaliação de eco eficiência (AEE). Eco eficiência é o \"aspecto da sustentabilidade que relaciona o desempenho ambiental de um sistema de produto ao valor do sistema de produto\" (ISO, 2012). Estão disponíveis diferentes métodos de AEE, porém sem evidência das suas semelhanças e particularidades e como essas características influenciam na escolha do método mais adequado de AEE em relação às potenciais aplicações O objetivo desta pesquisa é, portanto, analisar e indicar os tipos de métodos de avaliação de eco eficiência (AEE) mais adequados para ações gerenciais nas quais caibam tais abordagens. Foram selecionados onze métodos de AEE, a partir do estabelecimento de critérios de caracterização desses métodos, a saber: BASF, Bayer, EcoWater, Hahn et al., Kuosmanen e Kortelainen, MIPS, NRTEE, UN ESCAP, UN, TU Delft, e WBCSD. Identificaram-se, ainda, quatro potenciais aplicações: (i) Monitoramento de processo com vistas à melhoria contínua; (ii) Selecção e classificação de produtos; (iii) Atendimento a requisitos legais e outros requisitos; e, (iv) Marketing, rotulagem de produtos e comunicação ambiental. A partir dos elementos metodológicos estabelecidos pela norma ISSO 14045 (2012) e do conhecimento obtido dos métodos de AEE, determinaram-se quatro requisitos pelos quais os métodos e os potenciais aplicações foram avaliados: (i) Tipo de indicador de desempenho ambiental; (ii) Tipo de indicador de valor de sistema de produto; (iii) Abrangência de aplicação; e, (iv) Tipo de indicador de eco eficiência. Aplicando-se estes requisitos nos métodos de AEE e nos potenciais usos, concluiu-se que quanto à aplicações em termos de monitoramento de processos com vistas à melhoria continua os métodos de AEE recomendados foram Bayer, NRTEE, WBCSD e UN. Para situações de seleção e classificação de produtos os métodos BASF, EcoWater, Kuosmanen e Kortelainen, MIPS, Hahn et al., TU Delft, UN ESCAP e UN demonstraram ter boa aderência. No que se refere a usos voltados ao atendimento de requisitos legais e/ou de outras naturezas, os métodos NRTEE, WBCSD e UN são os mais indicados. Em aplicações de marketing, rotulagem e comunicação foram indicados os métodos BASF, EcoWater e MIPS. Finalmente, concluiu-se que, para a escolha adequada da metodologia para uma AEE, conhecimento prévio das características de cada abordagem é necessário.

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To maintain the pace of development set by Moore's law, production processes in semiconductor manufacturing are becoming more and more complex. The development of efficient and interpretable anomaly detection systems is fundamental to keeping production costs low. As the dimension of process monitoring data can become extremely high anomaly detection systems are impacted by the curse of dimensionality, hence dimensionality reduction plays an important role. Classical dimensionality reduction approaches, such as Principal Component Analysis, generally involve transformations that seek to maximize the explained variance. In datasets with several clusters of correlated variables the contributions of isolated variables to explained variance may be insignificant, with the result that they may not be included in the reduced data representation. It is then not possible to detect an anomaly if it is only reflected in such isolated variables. In this paper we present a new dimensionality reduction technique that takes account of such isolated variables and demonstrate how it can be used to build an interpretable and robust anomaly detection system for Optical Emission Spectroscopy data.

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The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

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Despite the efforts to better manage biosolids field application programs, biosolids managers still lack of efficient and reliable tools to apply large quantities of material while avoiding odor complaints. Objectives of this research were to determine the capabilities of an electronic nose in supporting process monitoring of biosolids production and, to compare odor characteristics of biosolids produced through thermal-hydrolysis anaerobic digestion (TH-AD) to those of alkaline stabilization in the plant, under storage and in the field. A method to quantify key odorants was developed and full scale sampling and laboratory simulations were performed. The portable electronic nose (PEN3) was tested for its capabilities of distinguishing alkali dosages in the biosolids production process. Frequency of recognition of unknown samples was tested achieving highest accuracy of 81.1%. This work exposed the need for a different and more sensitive electronic nose to assure its applicability at full scale for this process. GC-MS results were consistent with those reported in literature and helped to elucidate the behavior of the pattern recognition of the PEN3. Odor characterization of TH-AD and alkaline stabilized biosolids was achieved using olfactometry measurements and GC-MS. Dilution-to-threshold of TH-AD biosolids increased under storage conditions but no correlation was found with the target compounds. The presence of furan and three methylated homologues in TH-AD biosolids was reported for the first time proposing that these compounds are produced during thermal hydrolysis process however, additional research is needed to fully describe the formation of these compounds and the increase in odors. Alkaline stabilized biosolids reported similar odor concentration but did not increase and the ‘fishy’ odor from trimethylamine emissions resulted in more offensive and unpleasant odors when compared to TH-AD. Alkaline stabilized biosolids showed a spike in sulfur and trimethylamine after 3 days of field application when the alkali addition was not sufficient to meet regulatory standards. Concentrations of target compounds from field application of TH-AD biosolids gradually decreased to below the odor threshold after 3 days. This work increased the scientific understanding on odor characteristics and behavior of two types of biosolids and on the application of electronic noses to the environmental engineering field.

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Tese (doutorado)—Universidade de Brasília, Faculdade de Ciências da Saúde, Programa de Pós-Graduação em Ciências da Saúde, 2016.

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A presente dissertação de mestrado tem como finalidade primordial mapear a intervenção técnica com base processual, junto de uma família beneficiária de rendimento social de inserção. Mais especificamente aferir as problemáticas e vulnerabilidades da família ao longo do acompanhamento, confrontando com a avaliação diagnóstica e a elaboração de todo o acompanhamento. A investigação segue uma metodologia de estudo de caso com análise documental de um processo acompanhado há 18 anos, cruzando as evidências da intervenção aferindo avaliação diagnostica, a conceção do plano de intervenção e respetivo processo de monitorização, acompanhamento e avaliação. O presente estudo apresenta a necessidade de estruturação de instrumentos de monitorização de todo acompanhamento e uma reflexão sobre as implicações da medida relativamente ao comportamento das famílias beneficiária.

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This thesis explored the development of statistical methods to support the monitoring and improvement in quality of treatment delivered to patients undergoing coronary angioplasty procedures. To achieve this goal, a suite of outcome measures was identified to characterise performance of the service, statistical tools were developed to monitor the various indicators and measures to strengthen governance processes were implemented and validated. Although this work focused on pursuit of these aims in the context of a an angioplasty service located at a single clinical site, development of the tools and techniques was undertaken mindful of the potential application to other clinical specialties and a wider, potentially national, scope.

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One of the main challenges facing online and offline path planners is the uncertainty in the magnitude and direction of the environmental energy because it is dynamic, changeable with time, and hard to forecast. This thesis develops an artificial intelligence for a mobile robot to learn from historical or forecasted data of environmental energy available in the area of interest which will help for a persistence monitoring under uncertainty using the developed algorithm.