983 resultados para production product data


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Mestrado em Engenharia Química - Ramo optimização energética na indústria química

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Dissertação para obtenção do grau de Mestre em Engenharia Química

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Atualmente o sistema produtivo do tipo job shop é muito comum nas PMEs (Pequenas e Médias Empresas). Estas empresas trabalham por encomenda. Produzem grande variedade de modelos, e em pequenas quantidades. Os prazos de entrega são um fator de elevada importância, pois os clientes exigem um produto de qualidade no tempo certo. O presente trabalho, pretende criar uma ferramenta de programação da produção para a secção da costura, usando dados reais da empresa, que tem uma implantação do tipo job shop com máquinas multi-operação (Multi-Purpose -Machines Job Shop). No final, são reunidas as principais conclusões e perspetivados futuros desenvolvimentos. Os resultados obtidos comprovam que o algoritmo desenvolvido, com base no algoritmo de Giffler & Thompson, consegue obter com grande precisão e de forma rápida o escalonamento / balanceamento da secção da costura. Com a ferramenta criada, a empresa otimiza a programação da secção da costura e fornece informação importante á gestão da produção, possibilitando uma melhoria do planeamento da empresa.

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Mestrado em Contabilidade e Gestão das Instituições Financeiras

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertation presented in partial fulfillment of the requirements for the degree of Master in Biotechnology

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Biotecnologia

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ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

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The most important processes for the creation of S12+ to S14+ ions excited states from the ground configurations of S9+ to S14+ ions in an electron cyclotron resonance ion source, leading to the emission of K X-ray lines, are studied. Theoretical values for inner-shell excitation and ionization cross sections, including double KL and triple KLL ionization, transition probabilities and energies for the deexcitation processes, are calculated in the framework of the multi-configuration Dirac-Fock method. With reasonable assumptions about the electron energy distribution, a theoretical K$\alpha$ X-ray spectrum is obtained, which is compared to recent experimental data.

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Most of the traditional software and database development approaches tend to be serial, not evolutionary and certainly not agile, especially on data-oriented aspects. Most of the more commonly used methodologies are strict, meaning they’re composed by several stages each with very specific associated tasks. A clear example is the Rational Unified Process (RUP), divided into Business Modeling, Requirements, Analysis & Design, Implementation, Testing and Deployment. But what happens when the needs of a well design and structured plan, meet the reality of a small starting company that aims to build an entire user experience solution. Here resource control and time productivity is vital, requirements are in constant change, and so is the product itself. In order to succeed in this environment a highly collaborative and evolutionary development approach is mandatory. The implications of constant changing requirements imply an iterative development process. Project focus is on Data Warehouse development and business modeling. This area is usually a tricky one. Business knowledge is part of the enterprise, how they work, their goals, what is relevant for analyses are internal business processes. Throughout this document it will be explained why Agile Modeling development was chosen. How an iterative and evolutionary methodology, allowed for reasonable planning and documentation while permitting development flexibility, from idea to product. More importantly how it was applied on the development of a Retail Focused Data Warehouse. A productized Data Warehouse built on the knowledge of not one but several client needs. One that aims not just to store usual business areas but create an innovative sets of business metrics by joining them with store environment analysis, converting Business Intelligence into Actionable Business Intelligence.

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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This paper describes preliminary work on the generation of synthesis gas from water electrolysis using graphite electrodes without the separation of the generated gases. This is an innovative process, that has no similar work been done earlier. Preliminary tests allowed to establish correlations between the applied current to the electrolyser and flow rate and composition of the generated syngas, as well as a characterisation of generated carbon nanoparticles. The obtained syngas can further be used to produce synthetic liquid fuels, for example, methane, methanol or DME (dimethyl ether) in a catalytic reactor, in further stages of a present ongoing project, using the ELECTROFUEL® concept. The main competitive advantage of this project lies in the built-in of an innovative technology product, from RE (renewable energy) power in remote locations, for example, islands, villages in mountains as an alternative for energy storage for mobility constraints.

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The proper disposal of the several types of wastes produced in industrial activities increases production costs. As a consequence, it is common to develop strategies to reuse these wastes in the same process and in different processes or to transform them for use in other processes. This work combines the needs for new synthesis methods of nanomaterials and the reduction of production cost using wastes from citrine juice (orange, lime, lemon and mandarin) to produce a new added value product, green zero-valent iron nanoparticles that can be used in several applications, including environmental remediation. The results indicate that extracts of the tested fruit wastes (peel, albedo and pulp fractions) can be used to produce zero-valent iron nanoparticles (nZVIs). This shows that these wastes can be an added value product. The resulting nZVIs had sizes ranging from 3 up to 300 nm and distinct reactivities (pulp > peel > albedo extracts). All the studied nanoparticles did not present a significant agglomeration/settling tendency when compared to similar nanoparticles, which indicates that they remain in suspension and retain their reactivity.

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Relatório de estágio apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

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This paper presents an optimization study of a distillation column for methanol and aqueous glycerol separation in a biodiesel production plant. Considering the available physical data of the column configuration, a steady state model was built for the column using Aspen-HYSYS as process simulator. Several sensitivity analysis were performed in order to better understand the relation between the variables of the distillation process. With the information obtained by the simulator, it is possible to define the best range for some operational variables that maintain composition of the desired product under specifications and choose operational conditions to minimize energy consumptions.