512 resultados para machining jig


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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Engenharia Mecânica - FEIS

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Pós-graduação em Engenharia Mecânica - FEIS

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Pós-graduação em Engenharia Mecânica - FEIS

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Ceramic parts are increasingly replacing metal parts due to their excellent physical, chemical and mechanical properties, however they also make them difficult to manufacture by traditional machining methods. The developments carried out in this work are used to estimate tool wear during the grinding of advanced ceramics. The learning process was fed with data collected from a surface grinding machine with tangential diamond wheel and alumina ceramic test specimens, in three cutting configurations: with depths of cut of 120 mu m, 70 mu m and 20 mu m. The grinding wheel speed was 35m/s and the table speed 2.3m/s. Four neural models were evaluated, namely: Multilayer Perceptron, Radial Basis Function, Generalized Regression Neural Networks and the Adaptive Neuro-Fuzzy Inference System. The models'performance evaluation routines were executed automatically, testing all the possible combinations of inputs, number of neurons, number of layers, and spreading. The computational results reveal that the neural models were highly successful in estimating tool wear, since the errors were lower than 4%.

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In experimental conditions, cutting forces were studied during turning of green alumina billets, including their correlation with surface aspects of the workpiece. The correlation between cutting power and the removal rate are important parameters for defining the design of ceramic products, since inadequate parameters can produce excessive surface damage to the workpiece. This study examined the forces obtained during turning of alumina workpieces with 99.8% purity in their green state, by means of a three-point dynamometer, evaluating the cutting, feed and depth forces, using a cermet tool under constant machining conditions. Variables were compared with the forces, including surface finish, tool wear and temperature during machining. In the study, it was found that the depth of cut had no significant effect on the surface quality, and the cutting speed and feed influencing the finish. However, preliminary tests for selecting the cutting conditions showed that unsuitables cutting speeds and feeds generate severe damage to the workpiece surface. The best condition was 1.00 mm depth of cut, and the forces increasedfor with each pass performed, with the feed force the variable with greatest increases in relation to the cutting and depth forces, and wear of the cutting tool directly influenced the surface finish, generated by the highly abrasive nature of the alumina particles of the green compact. It is emphasized that the alumina in its green state showed high abrasive effect on the cutting tool during the turning process and the surface finishing of the green workpiece had a direct influence on the sintered workpiece.

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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Engenharia Mecânica - FEG

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Pós-graduação em Engenharia Mecânica - FEG