927 resultados para Business planning -- Basque Country


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Trabalho Final de Mestrado para obtenção de grau de Mestre em Engenharia Mecânica na Especialidade de Manutenção e Produção

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A Cooperativa Agrícola de Vila do Conde desenvolve um negócio de fabrico e comercialização de misturas complementares para alimentação bovina, sobretudo para vacas leiteiras. Há alguns anos a esta parte, esta Cooperativa sabe que terá que deslocalizar a unidade fabril existente devido a imposições da Direção Geral de Alimentação e Veterinária, relacionadas com questões de natureza ambiental. A necessidade de ser realizado um novo investimento, para garantir a sustentabilidade do negócio mais rentável gerido por esta Cooperativa, levou a pensar-se na possibilidade de construção de uma nova unidade fabril, de dimensão superior, capaz de servir outras cooperativas, visando o desejado entendimento das cooperativas em torno de um objetivo comum, logrando a obtenção de economias de escala, de extrema importância para a sobrevivência do setor leiteiro na região do Entre Douro e Minho. Para o efeito será constituída uma nova sociedade por quotas, designada por AGRIVIL XXI, Lda., de capital exclusivamente cooperativo, possibilitando que, em cada momento, se possa aferir a situação económica e financeira do negócio de forma mais rigorosa e autónoma. Esta realidade foi conducente à elaboração do presente Plano de Negócios que se espera profícuo para definição dos objetivos e metas a atingir num futuro próximo pela Cooperativa Agrícola de Vila do Conde. As análises de viabilidade e do risco do projeto demonstraram estarem criadas as condições de aceitação do mesmo, sendo expectável um VAL de 1.371.764 euros, uma TIR de 12,04% e um pay-back period próximo dos 11 anos. No entanto é notório a existência de um risco inerente ao investimento na medida em que o montante dos fluxos gerados tende a aproximar-se dos fluxos investidos, não gerando um excedente de riqueza significativo.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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Mestrado em Controlo e Gestão dos Negócios

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Kinematic redundancy occurs when a manipulator possesses more degrees of freedom than those required to execute a given task. Several kinematic techniques for redundant manipulators control the gripper through the pseudo-inverse of the Jacobian, but lead to a kind of chaotic inner motion with unpredictable arm configurations. Such algorithms are not easy to adapt to optimization schemes and, moreover, often there are multiple optimization objectives that can conflict between them. Unlike single optimization, where one attempts to find the best solution, in multi-objective optimization there is no single solution that is optimum with respect to all indices. Therefore, trajectory planning of redundant robots remains an important area of research and more efficient optimization algorithms are needed. This paper presents a new technique to solve the inverse kinematics of redundant manipulators, using a multi-objective genetic algorithm. This scheme combines the closed-loop pseudo-inverse method with a multi-objective genetic algorithm to control the joint positions. Simulations for manipulators with three or four rotational joints, considering the optimization of two objectives in a workspace without and with obstacles are developed. The results reveal that it is possible to choose several solutions from the Pareto optimal front according to the importance of each individual objective.

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Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems

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The trajectory planning of redundant robots through the pseudoinverse control leads to undesirable drift in the joint space. This paper presents a new technique to solve the inverse kinematics problem of redundant manipulators, which uses a fractional differential of order α to control the joint positions. Two performance measures are defined to examine the strength and weakness of the proposed method. The positional error index measures the precision of the manipulator's end-effector at the target position. The repeatability performance index is adopted to evaluate if the joint positions are repetitive when the manipulator execute repetitive trajectories in the operational workspace. Redundant and hyper-redundant planar manipulators reveal that it is possible to choose in a large range of possible values of α in order to get repetitive trajectories in the joint space.

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In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.

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The trajectory planning of redundant robots is an important area of research and efficient optimization algorithms are needed. The pseudoinverse control is not repeatable, causing drift in joint space which is undesirable for physical control. This paper presents a new technique that combines the closed-loop pseudoinverse method with genetic algorithms, leading to an optimization criterion for repeatable control of redundant manipulators, and avoiding the joint angle drift problem. Computer simulations performed based on redundant and hyper-redundant planar manipulators show that, when the end-effector traces a closed path in the workspace, the robot returns to its initial configuration. The solution is repeatable for a workspace with and without obstacles in the sense that, after executing several cycles, the initial and final states of the manipulator are very close.

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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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Dissertação de Mestrado em Empreendedorismo e Internacionalização apresentada ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Empreendedorismo e Internacionalização, sob orientação de Professora Doutora Celsa Maria Carvalho Machado e Mestre Maria Luísa Verdelho Alves

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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