3 resultados para Modelo Digital de Superfície

em Repositório Institucional da Universidade Tecnológica Federal do Paraná (RIUT)


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Supply chains have become an important focus for competitive advantage. The performance of a company increasingly depends on its ability to maintain effective and efficient relationships with its suppliers and customers. The extended enterprise (i.e. composed of several partners) needs to be dynamically formed in order to be agile and adaptable. According to the Digital Manufacturing paradigm, companies have to be able to quickly share and disseminate information regarding planning, designing and manufacturing of products. Additionally, they must be responsive to all technical and business determinants, as well as be assessed and certified for guaranteed performance. The current research intends to present a solution for the dynamic composition of the extended enterprise, formed to take advantage of market opportunities quickly and efficiently. A construction model was developed. This construction model consists of: information model, protocol model and process model. The information model has been defined based on the concepts of Supply Chain Operations Reference model (SCOR®). In this model is defined information for negotiating the participation of candidate companies in the dynamic establishment of a network for responding to a given demand for developing and manufacturing products, in seven steps as follows: request for information; request for qualification; alignment of strategy; request for proposal; request for quotation; compatibility of process; and compatibility of system. The protocol model has been elaborated and inspired in the OSI, this model provides a framework for linking customers and suppliers, indicates a sequence to be followed, in order to selecte companies to become suppliers. The process model has been implemented by means of process modeling according to the BPMN standard and, in turn, implemented as a web-based application that runs the process through its several steps, which uses forms to gather data. An application example in the context of the oil and gas industry is used for demonstrating the solution concept.

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Physiologists and animal scientists try to understand the relationship between ruminants and their environment. The knowledge about feeding behavior of these animals is the key to maximize the production of meat and milk and their derivatives and ensure animal welfare. Within the area called precision farming, one of the goals is to find a model that describes animal nutrition. Existing methods for determining the consumption and ingestive patterns are often time-consuming and imprecise. Therefore, an accurate and less laborious method may be relevant for feeding behaviour recognition. Surface electromyography (sEMG) is able to provide information of muscle activity. Through sEMG of the muscles of mastication, coupled with instrumentation techniques, signal processing and data classification, it is possible to extract the variables of interest that describe chewing activity. This work presents a new method for chewing pattern evaluation, feed intake prediction and for the determination of rumination, food and daily rest time through ruminant animals masseter muscle sEMG signals. Short-term evaluation results are shown and discussed, evidencing employed methods viability.

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In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.