24 resultados para LINE-UP
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Dissertação de mestrado em Ciências da Comunicação (área de especialização em Publicidade e Relações Públicas)
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As increasingly more sophisticated materials and products are being developed and times-to-market need to be minimized, it is important to make available fast response characterization tools using small amounts of sample, capable of conveying data on the relationships between rheological response, process-induced material structure and product characteristics. For this purpose, a single / twin-screw mini-extrusion system of modular construction, with well-controlled outputs in the range 30-300 g/h, was coupled to a in- house developed rheo-optical slit die able to measure shear viscosity and normal-stress differences, as well as performing rheo-optical experiments, namely small angle light scattering (SALS) and polarized optical microscopy (POM). In addition, the mini-extruder is equipped with ports that allow sample collection, and the extrudate can be further processed into products to be tested later. Here, we present the concept and experimental set-up [1, 2]. As a typical application, we report on the characterization of the processing of a polymer blend and of the properties of extruded sheets. The morphological evolution of a PS/PMMA industrial blend along the extruder, the flow-induced structures developed and the corresponding rheological characteristics are presented, together with the mechanical and structural characteristics of produced sheets. The application of this experimental tool to other material systems will also be discussed.
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Dissertação de mestrado em Bioquímica Aplicada – Biomedicina
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Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos.
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Relatório de estágio de mestrado em Educação Pré-Escolar e Ensino do 1.º do Ensino Básico
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Earthworks tasks are often regarded in transportation projects as some of the most demanding processes. In fact, sequential tasks such as excavation, transportation, spreading and compaction are strongly based on heavy mechanical equipment and repetitive processes, thus becoming as economically demanding as they are time-consuming. Moreover, actual construction requirements originate higher demands for productivity and safety in earthwork constructions. Given the percentual weight of costs and duration of earthworks in infrastructure construction, the optimal usage of every resource in these tasks is paramount. Considering the characteristics of an earthwork construction, it can be looked at as a production line based on resources (mechanical equipment) and dependency relations between sequential tasks, hence being susceptible to optimization. Up to the present, the steady development of Information Technology areas, such as databases, artificial intelligence and operations research, has resulted in the emergence of several technologies with potential application bearing that purpose in mind. Among these, modern optimization methods (also known as metaheuristics), such as evolutionary computation, have the potential to find high quality optimal solutions with a reasonable use of computational resources. In this context, this work describes an optimization algorithm for earthworks equipment allocation based on a modern optimization approach, which takes advantage of the concept that an earthwork construction can be regarded as a production line.
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Companies from the motorcycles components branch are dealing with a dynamic environment, resulting from the introduction of new products and the increase of market demand. This dynamic environment requires frequent changes in production lines and requires flexibility in the processes, which can cause reductions in the level of quality and productivity. This paper presents a Lean Six Sigma improvement project performed in a production line of the company's machining sector, in order to eliminate losses that cause low productivity, affecting the fulfillment of the production plan and customer satisfaction. The use of Lean methodology following the DMAIC stages allowed analyzing the factors that influence the line productivity loss. The major problems and causes that contribute to a reduction on productivity and that were identified in this study are the lack of standardization in the setup activities and the excessive stoppages for adjustment of the processes that caused an increase of defects. Control charts, Pareto analysis and cause-and-effect diagrams were used to analyze the problem. On the improvement stage, the changes were based on the reconfiguration of the line layout as well as the modernization of the process. Overall, the project justified an investment in new equipment, the defective product units were reduced by 84% and an increase of 29% of line capacity was noticed.
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In this work, a steel heated pultrusion die was designed, developed and manufactured to produce U200 glass fibre reinforced thermosetting matrix (GRP) profiles. The finite element analysis (FEA) was used to predict and optimise the developed die heating by using cylindrical electrical powered cartridges. To assess the new die performance it was mounted in the 120 kN pultrusion line of the Portuguese company Vidropol SA and used to produce continuously U200 profiles able to meet all requirements specified for the E23 grade accordingly to the European Standard EN 13706: 2002. After setting up the type, orientation and sequence of layers in laminate, orthophthalic, isophthalic and bisphenolic unsaturated polyester as well as vinylester resins were used to produce glass fibre reinforced U 200 composite profiles. An appropriated catalyst system was selected and the processing variables optimised for each case, namely, pultrusion pull-speed and die temperature. Finally, the produced U200 profiles were submitted to visual inspection, calcination and mechanical tests, namely, flexural, tensional and interlaminar shear strength (ILSS) tests, to assess their accomplishment with the EN 13706 requirements.
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In this work, a new steel heated pultrusion die was designed, developed and manufactured to produce U200 glass fibre reinforced thermosetting matrix (GRP) profiles. The finite element analysis (FEA) was used to predict and optimise the developed die heating by using cylindrical electrical powered cartridges. To assess the new die performance it was mounted in the 120 kN pultrusion line of the Portuguese company Vidropol SA and used to produce continuously U200 profiles able to meet all requirements specified for the E23 grade accordingly to the European Standard EN 13706: 2002. After setting up the type, orientation and sequence of layers in the U 200 laminate, different types of thermosetting resins were used in its production. Orthophthalic, isophthalic and bisphenolic unsaturated polyester as well as vinylester resins were used to produce glass fibre reinforced U 200 composite profiles. All applied resins were submitted to SPI gel tests in order to select the more appropriated catalyst system and optimise the processing variables to be used in each case, namely, pultrusion pull-speed and die temperature. The best pultrusion operational conditions were selected by varying and monitoring the pull-speed and die temperature and, at the same time, measuring the temperature on the manufactured U 200 profile during processing. Finally, the produced U200 profiles were submitted to visual inspection, calcination and mechanical tests, namely, flexural, tensional and interlaminar shear strength (ILSS) tests, to assess their accomplishment with the EN 13706 requirements.
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Companies and researchers involved in developing miniaturized electronic devices face the basic problem of the needed batteries size, finite life of time and environmental pollution caused by their final deposition. The current trends to overcome this situation point towards Energy Harvesting technology. These harvesters (or scavengers) store the energy from sources present in the ambient (as wind, solar, electromagnetic, etc) and are costless for us. Piezoelectric devices are the ones that show a higher power density, and materials as ceramic PZT or polymeric PVDF have already demonstrated their ability to act as such energy harvester elements. Combinations between piezoelectric and electromagnetic mechanism have been also extensively investigated. Nevertheless, the power generated by these combinations is limited under the application of small magnetic fields, reducing the performance of the energy harvester [1]. In the last years the appearance of magnetoelectric (ME) devices, in which the piezoelectric deformation is driven by the magnetostrictive element, enables to extract the energy of very small electromagnetic signals through the generated magnetoelectric voltage at the piezoelectric element. However, very little work has been done testing PVDF polymer as piezoelectric constituent of the ME energy harvester device, and only to be proposed as a possibility of application [2]. Among the advantages of using piezopolymers for vibrational energy harvesting we can remember that they are ductile, resilient to shock, deformable and lightweight. In this work we demonstrate the feasibility of using magnetostrictive Fe-rich magnetic amorphous alloys/piezoelectric PVDF sandwich-type laminated ME devices as energy harvesters. A very simple experimental set-up will show how these laminates can extract energy, in amounts of μW, from an external AC field.
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There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.
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Dissertação de mestrado em Direito Administrativo
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Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Biomateriais, Reabilitação e Biomecânica)
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Dissertação de mestrado em Design de Comunicação de Moda
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Tese de Doutoramento em Biologia de Plantas