753 resultados para new product performance


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Pós-graduação em Engenharia de Produção - FEG

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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ABSTRACT: This thesis report illustrates the applications and potentials of biogenic methane recovery in Nebraska’s agricultural and industrial sectors and as a means for increasing sustainable economic development in the state’s rural communities. As the nation moves toward a new green economy, biogenic methane recovery as a waste management strategy and renewable energy resource presents significant opportunities for Nebraska to be a national and world leader in agricultural and industrial innovation, advanced research and development of renewable energy technology, and generation of new product markets. Nebraska’s agricultural economy provides a distinct advantage to the state for supporting methane recovery operations that provide long-term economic and environmental partnerships among producers, industry, and communities. These opportunities will serve to protect Nebraska’s agricultural producers from volatile energy input markets and as well as creating new markets for Nebraska agricultural products. They will also serve to provide quality education and employment opportunities for Nebraska students and businesses. There are challenges and issues that remain for the state in order to take advantage of its resource potential. There is a need to produce a comprehensive Nebraska biogenic methane potential study and digital mapping system to identify high-potential producers, co-products, and markets. There is also a need to develop a web-based format of consolidated information specific to Nebraska to aid in connecting producers, service providers, educators, and policy-makers.

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With the increasing emphasis on health and well-being, nutrition aspects need to be incorporated as a dimension of product development. Thus, the production of a high-fibre content snack food from a mixture of corn and flaxseed flours was optimized by response surface methodology. The independent variables considered in this study were: feed moisture, process temperature and flaxseed flour addition, as they were found to significantly impact the resultant product. These variables were studied according to a rotatable composite design matrix (-1.68, -1, 0, 1, 1.68). Response variable was the expansion ratio since it has been highly correlated with acceptability. The optimum corn-flaxseed snack obtained presented a sevenfold increase in dietary fibre, almost 100% increase in protein content compared to the pure corn snack, and yielded an acceptability score of 6.93. This acceptability score was similar to those observed for corn snack brands in the market, indicating the potential commercial use of this new product, which can help to increase the daily consumption of dietary fibre.

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Diversos estudos têm sido realizados no intuito de analisar os impactos da inovação tecnológica no desempenho comercial das empresas. Com isso, este estudo visa analisar os fatores de influência sobre o percentual do faturamento com a venda de novos produtos na indústria do Estado de São Paulo. Trata-se de uma pesquisa com características descritivas e explicativas, cuja abordagem é quantitativa, utilizando dados secundários provindos da Pesquisa de Atividade Econômica Paulista (PAEP), realizada pela Fundação SEADE. Os resultados mostram que os fatores de influência sobre o faturamento provindo de novos produtos são: a origem do capital controlador; a empresa pertencer a um grupo empresarial; o total de pessoal em pesquisa e desenvolvimento; o pessoal alocado diretamente na produção; as fontes de informação para atividades inovativas; e o apoio governamental para a inovação tecnológica.

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Rural tourism is relatively new product in the process of diversification of the rural economy in Republic of Macedonia. This study used desk research and life story interviews of rural tourism entrepreneurs as qualitative research method to identify prevalent success influential factors. Further quantitative analysis was applied in order to measure the strength of influence of identified success factors. The primary data for the quantitative research was gathered using telephone questionnaire composed of 37 questions with 5-points Likert scale. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) by SmartPLS 3.1.6. Results indicated that human capital, social capital, entrepreneurial personality and external business environment are predominant influential success factors. However, human capital has non-significant direct effect on success (p 0.493) nonetheless the effect was indirect with high level of partial mediation through entrepreneurial personality as mediator (VAF 73%). Personality of the entrepreneur, social capital and business environment have direct positive affect on entrepreneurial success (p 0.001, 0.003 and 0.045 respectably). Personality also mediates the positive effect of social capital on entrepreneurial success (VAF 28%). Opposite to the theory the data showed no interaction between social and human capital on the entrepreneurial success. This research suggests that rural tourism accommodation entrepreneurs could be more successful if there is increased support in development of social capital in form of conservation of cultural heritage and natural attractions. Priority should be finding the form to encourage and support the establishment of formal and informal associations of entrepreneurs in order to improve the conditions for management and marketing of the sector. Special support of family businesses in the early stages of the operation would have a particularly positive impact on the success of rural tourism. Local infrastructure, access to financial instruments, destination marketing and entrepreneurial personality have positive effect on success.

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The competitive industrial context compels companies to speed-up every new product design. In order to keep designing products that meet the needs of the end user, a human centered concurrent product design methodology has been proposed. Its setting up is complicated by the difficulties of collaboration between experts involved inthe design process. In order to ease this collaboration, we propose the use of virtual reality as an intermediate design representation in the form of light and specialized immersive convergence support applications. In this paper, we present the As Soon As Possible (ASAP) methodology making possible the development of these tools while ensuring their usefulness and usability. The relevance oft his approach is validated by an industrial use case through the design of an ergonomic-style convergence support tool.

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In 1961 Allan Kaprow (1927–2006) and Claes Oldenburg (b. 1929) exchanged a number of letters in which they argued about the definition of their avant-garde practices as Happenings. Kaprow, who first introduced this "root-metaphor," as he would later call it, describes with it the necessity of the respective activity to be as far removed as possible from all motives, materials, and formats conventionally connected to art. Oldenburg, who at the time of this exchange was just as active in the New York performance scene as Kaprow, disagrees with his colleague's removal of their practice from the artistic sphere. Oldenburg is also dissatisfied with the fact that Kaprow, through his writings, launches a critical discourse that follows his own definition of the Happening. The two artists thus argue just as much about the positioning of their practices with respect to art as over the authority to establish such a position. This essay traces their argument through their written conversation and in doing so exposes the immense influence Kaprow's rhetoric had on the subsequent art-historical canonization of their respective practices: Oldenburg's more ambivalent position is today amalgamated with Kaprow's theoretical stance.

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Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.

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Molybdenum is a low Tc, type I superconductor whose fundamental properties are poorly known. Its importance as an essential constituent of new high performance radiation detectors, the so-called transition edge sensors (TESs) calls for better characterization of this superconductor, especially in thin film form. Here we report on a study of the basic superconducting features of Mo thin films as a function of their thickness. The resistivity is found to rise and the critical temperature decreases on decreasing film thickness, as expected. More relevant, the critical fields along and perpendicular to the film plane are markedly different, thickness dependent and much larger than the thermodynamic critical field of Mo bulk. These results are consistent with a picture of type II 2D superconducting films, and allow estimates of the fundamental superconducting lengths of Mo. The role of morphology in determining the 2D and type II character of the otherwise type I molybdenum is discussed. The possible consequences of this behaviour on the performance of radiation detectors are also addressed

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Nowadays, one of the main objectives that affects the development of any new product is the respect for the environment. Until the late 80's, the development and manufacture of the most of the product were aimed to achieve maximum quality in time and costs with environmental issues relegated to secondary importance. On the other hand, in the 90's, the pressure from factors such as markets, financial and legislative factors, led to environmental considerations being taken into account. In this context, the current aeronautical industry strategies are based on the search for economic, environmental and energy efficiency considerations for all the processes involved in the aircraft manufacturing.

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A suite of ferromanganese nodules were sampled during the MVSEIS-2008 cruise aboard of the R/V Hespérides in the flanks of Meknes mud volcano (Moroccan margin, NE Central Atlantic). The nodules were collected at water depths between 750-850 m within a seabed area characterized by high acoustic backscatter values. Debris of cold water corals and hydrocarbon-derived authigenic carbonate crusts were sampled at same time. The nodules show tabular morphology, up to 20 cm in maximum diameter and 2 kg of weight, brown-reddish external color and they are internally composed by a concentric to complex arrangement of laminae. The results of X-ray diffraction analysis show that these ferromanganese nodules are essentially composed of goethite and lepidocrocite, being Mn-oxides, silicates (quartz and clay minerals) and carbonates (calcite, dolomite and siderite) accessory to occasional minerals. All the samples display micritic to micro-sparitic mosaic under the petrographic microscope which forms massive, laminated or dendritic-mottled textures. The nodules show a high abundance of Fe, minor Mn and low contents of trace metals and REEs. Mature hydrocarbons, as n-alkanes derived from marine bacterial activity, and phenanthrene have been detected in all the ferromanganese nodules analyzed. These nodules display analogous characteristics (textural, mineralogical and geochemical) to the nodules studied by González et al (2009) in the carbonate mud-mounds in the Gulf of Cadiz, offshore Iberian margin. In this way, the same preliminary genetic model proposed for these nodules might be applicable to those find in the Meknes mud volcano. Therefore, the anaerobic oxidation of hydrocarbon-rich fluids within the mud-breccia sediments in the flanks of Meknes mud volcano would induce the formation of early diagenetic Fe-(Mn) carbonate nodules. Thus, the nodules were later exhumed by the erosive action of sea bottom currents generating the replacement of ferromanganese carbonates by Fe-Mn oxy-hydroxides. Thus, the hydrocarbon-rich fluid venting from deep seated reservoirs and erosive action of bottom currents must have been essential actors, as mineralization controls, for ferromanganese nodules generation and evolution. These findings imply that this type of nodules must be considered as new product as derived from the anaerobic/aerobic oxidation of hydrocarbons in areas of active seepages.

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El objetivo de este trabajo es determinar la influencia de la incorporación de nanoSiO2, nanoAl2O3 así como la mezcla de ambas adiciones, en morteros de cemento cuando son sometidos a ciclos de hielo-deshielo, e interpretar dicho comportamiento a través de los cambios microestructurales. Para ello se fabricaron cuatro morteros de cemento con distintas adiciones. Un mortero de cemento CEM I 52,5R normalizado de acuerdo a la Norma Europea EN 196-1:2005 como control. Otro de igual composición, al que se incorporó un 5% de nano-SiO2 respecto a la cantidad total de cemento, un tercero con un 5% de nano-Al2O3 y un cuarto con un 2,5% de nano-SiO2 y un 2,5% de nano-Al2O3. La relación agua/material cementante de 0,47. Para cada mortero, se fabricaron 4 probetas de 15x15x15 cm con el fin de determinar su resistencia a ciclos de hielodeshielo de acuerdo a la UNE-CEN/TS 12390-9 EX. Además, se caracterizaron microestructuralmente mediante porosimetría por intrusión de mercurio, análisis termogravimétrico y micrografía electrónica. Los resultados de la caracterización microestructural ponen de manifiesto un refinamiento de la matriz porosa, con aumento de la cantidad de geles hidratados. Las imágenes de SEM revelan cambios en la morfología de los productos hidratados de la matriz cementicia, siendo notables tanto en la portlandita como en la ettringita. Los cambios producidos por la adición de nano sílice muestran una gran influencia en la estructura porosa y determinan una mejora muy significativa en el comportamiento de estos morteros bajo ciclos hielo-deshielo. The rise of nanotechnology in the last two decades has been of scientific interest considerable for the construction industry due to the high potential in the use of nano-particles in cementitious materials. These allow a reengineering of existing products and the design of new high-performance materials. In this line there are many works in which we study the effect of additions of nano-particles in mortars and concretes. However, were very few scientific papers in which we study the behavior of these materials under freeze-thaw cycles. The aim of this study was to determine the influence of incorporating nano-SiO2, nano-Al2O3 and the mixture of both additions in cement mortar when subjected to freeze-thaw cycles, and interpret such behavior through microstructural changes.For this purpose four cement mortars have been fabricated with different additions. A cement mortar CEM I 52,5 R normalized according to the European standard EN 196-1:2005 was manufactured as control . Another mortar with a 5% nano-SiO2 in respect to the total amount of cement, other with 5% nano-Al2O3 and for last a mortar with 2.5% of nano-SiO2 and 2.5% of nano-Al2O3. The water/binder ratio was 0.47. For each mortar, four specimens were made of 150x150x150 mm in order to determine its behavior under freeze-thaw cycles according to UNE-CEN/TS EX 12390-9. Furthermore, the mortars were characterized microstructurally by mercury intrusion porosimetry, thermogravimetric analysis and electron micrograph. The microstructural characterization results show a refinement of the porous matrix, with increased amount of hydrated gels. The SEM images show changes in the morphology of the products of the hydrated cement matrix being remarkable both in the portlandite as in the ettringite. The changes produced by the addition of nanosilica show a great influence on the porous structure and determine a significant improvement in the behavior of these mortars under freeze-thaw cycles.

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It is our goal within this project to develop a powerful electronic system capable to claim, with high certainty, that a malicious software is running (or not) along with the workstations’ normal activity. The new product will be based on measurement of the supply current taken by a workstation from the grid. Unique technique is proposed within these proceedings that analyses the supply current to produce information about the state of the workstation and to generate information of the presence of malicious software running along with the rightful applications. The testing is based on comparison of the behavior of a fault-free workstation (established i advance) and the behavior of the potentially faulty device.

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El objetivo principal de esta tesis doctoral es profundizar en el análisis y diseño de un sistema inteligente para la predicción y control del acabado superficial en un proceso de fresado a alta velocidad, basado fundamentalmente en clasificadores Bayesianos, con el prop´osito de desarrollar una metodolog´ıa que facilite el diseño de este tipo de sistemas. El sistema, cuyo propósito es posibilitar la predicción y control de la rugosidad superficial, se compone de un modelo aprendido a partir de datos experimentales con redes Bayesianas, que ayudar´a a comprender los procesos dinámicos involucrados en el mecanizado y las interacciones entre las variables relevantes. Dado que las redes neuronales artificiales son modelos ampliamente utilizados en procesos de corte de materiales, también se incluye un modelo para fresado usándolas, donde se introdujo la geometría y la dureza del material como variables novedosas hasta ahora no estudiadas en este contexto. Por lo tanto, una importante contribución en esta tesis son estos dos modelos para la predicción de la rugosidad superficial, que se comparan con respecto a diferentes aspectos: la influencia de las nuevas variables, los indicadores de evaluación del desempeño, interpretabilidad. Uno de los principales problemas en la modelización con clasificadores Bayesianos es la comprensión de las enormes tablas de probabilidad a posteriori producidas. Introducimos un m´etodo de explicación que genera un conjunto de reglas obtenidas de árboles de decisión. Estos árboles son inducidos a partir de un conjunto de datos simulados generados de las probabilidades a posteriori de la variable clase, calculadas con la red Bayesiana aprendida a partir de un conjunto de datos de entrenamiento. Por último, contribuimos en el campo multiobjetivo en el caso de que algunos de los objetivos no se puedan cuantificar en números reales, sino como funciones en intervalo de valores. Esto ocurre a menudo en aplicaciones de aprendizaje automático, especialmente las basadas en clasificación supervisada. En concreto, se extienden las ideas de dominancia y frontera de Pareto a esta situación. Su aplicación a los estudios de predicción de la rugosidad superficial en el caso de maximizar al mismo tiempo la sensibilidad y la especificidad del clasificador inducido de la red Bayesiana, y no solo maximizar la tasa de clasificación correcta. Los intervalos de estos dos objetivos provienen de un m´etodo de estimación honesta de ambos objetivos, como e.g. validación cruzada en k rodajas o bootstrap.---ABSTRACT---The main objective of this PhD Thesis is to go more deeply into the analysis and design of an intelligent system for surface roughness prediction and control in the end-milling machining process, based fundamentally on Bayesian network classifiers, with the aim of developing a methodology that makes easier the design of this type of systems. The system, whose purpose is to make possible the surface roughness prediction and control, consists of a model learnt from experimental data with the aid of Bayesian networks, that will help to understand the dynamic processes involved in the machining and the interactions among the relevant variables. Since artificial neural networks are models widely used in material cutting proceses, we include also an end-milling model using them, where the geometry and hardness of the piecework are introduced as novel variables not studied so far within this context. Thus, an important contribution in this thesis is these two models for surface roughness prediction, that are then compared with respecto to different aspects: influence of the new variables, performance evaluation metrics, interpretability. One of the main problems with Bayesian classifier-based modelling is the understanding of the enormous posterior probabilitiy tables produced. We introduce an explanation method that generates a set of rules obtained from decision trees. Such trees are induced from a simulated data set generated from the posterior probabilities of the class variable, calculated with the Bayesian network learned from a training data set. Finally, we contribute in the multi-objective field in the case that some of the objectives cannot be quantified as real numbers but as interval-valued functions. This often occurs in machine learning applications, especially those based on supervised classification. Specifically, the dominance and Pareto front ideas are extended to this setting. Its application to the surface roughness prediction studies the case of maximizing simultaneously the sensitivity and specificity of the induced Bayesian network classifier, rather than only maximizing the correct classification rate. Intervals in these two objectives come from a honest estimation method of both objectives, like e.g. k-fold cross-validation or bootstrap.