48 resultados para Enterprise Resource Planning System


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As the complexity of embedded systems increases, multiple services have to compete for the limited resources of a single device. This situation is particularly critical for small embedded devices used in consumer electronics, telecommunication, industrial automation, or automotive systems. In fact, in order to satisfy a set of constraints related to weight, space, and energy consumption, these systems are typically built using microprocessors with lower processing power and limited resources. The CooperatES framework has recently been proposed to tackle these challenges, allowing resource constrained devices to collectively execute services with their neighbours in order to fulfil the complex Quality of Service (QoS) constraints imposed by users and applications. In order to demonstrate the framework's concepts, a prototype is being implemented in the Android platform. This paper discusses key challenges that must be addressed and possible directions to incorporate the desired real-time behaviour in Android.

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In this paper we consider global fixed-priority preemptive multiprocessor scheduling of constrained-deadline sporadic tasks that share resources in a non-nested manner. We develop a novel resource-sharing protocol and a corresponding schedulability test for this system. We also develop the first schedulability analysis of priority inheritance protocol for the aforementioned system. Finally, we show that these protocols are efficient (based on the developed schedulability tests) for a class of priority-assignments called reasonable priority-assignments.

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Wind resource evaluation in two sites located in Portugal was performed using the mesoscale modelling system Weather Research and Forecasting (WRF) and the wind resource analysis tool commonly used within the wind power industry, the Wind Atlas Analysis and Application Program (WAsP) microscale model. Wind measurement campaigns were conducted in the selected sites, allowing for a comparison between in situ measurements and simulated wind, in terms of flow characteristics and energy yields estimates. Three different methodologies were tested, aiming to provide an overview of the benefits and limitations of these methodologies for wind resource estimation. In the first methodology the mesoscale model acts like “virtual” wind measuring stations, where wind data was computed by WRF for both sites and inserted directly as input in WAsP. In the second approach, the same procedure was followed but here the terrain influences induced by the mesoscale model low resolution terrain data were removed from the simulated wind data. In the third methodology, the simulated wind data is extracted at the top of the planetary boundary layer height for both sites, aiming to assess if the use of geostrophic winds (which, by definition, are not influenced by the local terrain) can bring any improvement in the models performance. The obtained results for the abovementioned methodologies were compared with those resulting from in situ measurements, in terms of mean wind speed, Weibull probability density function parameters and production estimates, considering the installation of one wind turbine in each site. Results showed that the second tested approach is the one that produces values closest to the measured ones, and fairly acceptable deviations were found using this coupling technique in terms of estimated annual production. However, mesoscale output should not be used directly in wind farm sitting projects, mainly due to the mesoscale model terrain data poor resolution. Instead, the use of mesoscale output in microscale models should be seen as a valid alternative to in situ data mainly for preliminary wind resource assessments, although the application of mesoscale and microscale coupling in areas with complex topography should be done with extreme caution.

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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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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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The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.

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Este estudo tem como objetivos: (1) conhecer as práticas desenvolvidas numa organização do Ensino Superior Público Português; (2) conhecer a tipologia das práticas de GRH de cariz tradicional e de cariz estratégico; (3) perceber em que medida as práticas de GRH estão relacionadas com a área de qualificação dos responsáveis do departamento de RH; (4) averiguar o grau de satisfação que os trabalhadores sentem com as Práticas de Gestão de Recursos Humanos desenvolvidas e a sua relação com a área de qualificação dos responsáveis do departamento de RH. Foi utilizada uma metodologia mista, que possibilita ampliar a obtenção de resultados em abordagens investigativas, proporcionando ganhos relevantes para a pesquisa. É realizado um primeiro estudo exploratório, que utiliza uma metodologia mista quantitativa e qualitativa, com recurso a uma entrevista semiestruturada e inquérito realizados aos responsáveis de RH, e que tem como objetivos identificar e caracterizar as Práticas de GRH vigentes na Organização e, consequentemente, averiguar se se aproximam das designadas na literatura, assim como averiguar o grau de intervenção do DRH no desenvolvimento das PGRH e caraterizar o perfil do responsável de RH na Organização, averiguando se a área de formação de RH influencia as Práticas de GRH desenvolvidas. No segundo estudo, recorremos a uma metodologia quantitativa com recurso ao inquérito por questionário, aplicado aos trabalhadores que exercem funções a tempo integral, para averiguar o grau de satisfação dos trabalhadores em relação às Práticas de Gestão de Recursos Humanos. Na compilação dos dois estudos foi nosso objetivo obter respostas às questões que orientaram a nossa investigação. Na parte final da dissertação são discutidos os principais resultados obtidos e apresentadas as conclusões do estudo aqui levado a cabo. Os resultados sugerem que: 1) as PGRH existentes são essencialmente de cariz tradicional, em especial a gestão administrativa; 2) as PGRH predominantes são: o Planeamento de Recursos Humanos, a Análise e Descrição de Funções, o Recrutamento e Seleção, a Formação e Desenvolvimento, a Gestão Administrativa, a Comunicação e a Partilha de Informação, Ética e Deontologia e o Estatuto Disciplinar; 3) existe pouco recurso ao outsourcing para as PGRH; 4) o grau de intervenção DRH baseia-se em atividades de cariz mais administrativo; 5) as práticas tradicionais de RH são aquelas que requerem mais tempo ao DRH; 6) não existe relação entre o tipo de PGRH e a área de qualificação do responsável do DRH; 7) as PGRH são realizadas seguindo essencialmente as normas legais e regras rígidas da GRH na AP; 8) algumas PGRH não são entendidas em contexto da AP, como importantes pelos gestores, embora já sejam desenvolvidos alguns procedimentos dessas práticas; 9) a PGRH da formação e desenvolvimento não é corretamente desenvolvida e não dá cumprimento ao estipulado na lei; 10) a gestão de carreiras e o sistema de compensação e recompensas são entendidas como inexistentes, porque não existem promoções e progressões desde 2005; 11) a avaliação do desempenho é um sistema burocrático e ritualista com fins de promoção e compensação, sem efeitos práticos no momento atual, e que causa insatisfação e o sentimento de injustiça; 12) existem problemas de comunicação quanto a partilha e uniformização de procedimentos entre UO; 13) a satisfação dos trabalhadores é maior com as PGRH de tipo tradicional, nomeadamente na gestão administrativa, recrutamento e seleção, análise e descrição de funções, acolhimento, integração e socialização 14) a satisfação é menor na gestão de carreiras, no sistema de compensação e recompensas e na avaliação do desempenho; 15) quanto a relação entre o grau de satisfação e as características sócio demográficas e profissionais dos inquiridos, os casos com significância mostram que os trabalhadores com 10 ou mais anos de antiguidade tendem a sentir mais satisfação com as práticas em GRH; 16) existe mais satisfação dos trabalhadores das UO onde o responsável de DRH possui formação na área de RH.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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The development in power systems and the introduction of decentralized generation and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which considers not only the generation, but also the management of loads through demand response programs, energy storage units, EVs and other players in a liberalized electricity markets environment. This paper proposes a methodology to be used by Virtual Power Players (VPPs), concerning the energy resource scheduling in smart grids, considering day-ahead, hour-ahead and real-time scheduling. The case study considers a 33-bus distribution network with high penetration of distributed energy resources. The wind generation profile is based on a real Portuguese wind farm. Four scenarios are presented taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour-ahead and realtime scheduling.

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An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

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Gestão de Energia e Sustentabilidade são os pilares em que assenta esta dissertação, realizada no âmbito da Energia Elétrica em Ambiente Industrial. Neste sentido, deve entender-se “Gestão de Energia” como o planeamento de operações nas unidades de produção e de consumo. Tem como objetivos a conservação dos recursos, proteção climática e redução de custos, para que seja possível o acesso permanente à energia de que necessitamos. “Sustentabilidade”, por definição, é uma caraterística ou condição de um processo ou de um sistema que permite a sua permanência, até um determinado nível, por um determinado prazo. A Indústria Têxtil, da região do Vale do Ave, por ser extensa e muito heterogénea, quer na qualidade, quer na dimensão e nos recursos que utiliza, apresentou-se como uma oportunidade para aplicar os conhecimentos adquiridos, nas diversas disciplinas do Mestrado em Engenharia Electrotécnica - Área de Sistemas Eléctricos de Energia e como meio condutor à tentativa de optimização e racionalização do consumo de Energia Elétrica no Sector. O modelo encontrado para dar uma resposta satisfatória ao inicialmente proposto foi a Auditoria Energética. Neste sentido, foram realizadas visitas às instalações industriais, para o levantamento e recolha de informação, que posteriormente viria a ser analisada e, com base na mesma, tentou apresentar-se um conjunto de soluções que visassem a eficiência Energética do sector. Com o decorrer das visitas, surgiu a necessidade de criar um modelo, que servisse de guia da auditoria. Algo que seria um bloco de notas, mas específico, de forma a não perder a informação recolhida. Então foi desenvolvida uma aplicação para IPAD/IPHONE, o que permite também a recolha e armazenamento de fotografias, que aqui tem um papel fundamental. Salienta-se que as expectativas foram ao encontro do esperado, pois o que se encontrou foi um número significativo de empresas a precisar deste contributo. Atuando no “combate” ao consumo desnecessário e ao desperdício, é estar a contribuir ativa e positivamente, no desenvolvimento próspero da temática de Sustentabilidade Energética.

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All over the world, the liberalization of electricity markets, which follows different paradigms, has created new challenges for those involved in this sector. In order to respond to these challenges, electric power systems suffered a significant restructuring in its mode of operation and planning. This restructuring resulted in a considerable increase of the electric sector competitiveness. Particularly, the Ancillary Services (AS) market has been target of constant renovations in its operation mode as it is a targeted market for the trading of services, which have as main objective to ensure the operation of electric power systems with appropriate levels of stability, safety, quality, equity and competitiveness. In this way, with the increasing penetration of distributed energy resources including distributed generation, demand response, storage units and electric vehicles, it is essential to develop new smarter and hierarchical methods of operation of electric power systems. As these resources are mostly connected to the distribution network, it is important to consider the introduction of this kind of resources in AS delivery in order to achieve greater reliability and cost efficiency of electrical power systems operation. The main contribution of this work is the design and development of mechanisms and methodologies of AS market and for energy and AS joint market, considering different management entities of transmission and distribution networks. Several models developed in this work consider the most common AS in the liberalized market environment: Regulation Down; Regulation Up; Spinning Reserve and Non-Spinning Reserve. The presented models consider different rules and ways of operation, such as the division of market by network areas, which allows the congestion management of interconnections between areas; or the ancillary service cascading process, which allows the replacement of AS of superior quality by lower quality of AS, ensuring a better economic performance of the market. A major contribution of this work is the development an innovative methodology of market clearing process to be used in the energy and AS joint market, able to ensure viable and feasible solutions in markets, where there are technical constraints in the transmission network involving its division into areas or regions. The proposed method is based on the determination of Bialek topological factors and considers the contribution of the dispatch for all services of increase of generation (energy, Regulation Up, Spinning and Non-Spinning reserves) in network congestion. The use of Bialek factors in each iteration of the proposed methodology allows limiting the bids in the market while ensuring that the solution is feasible in any context of system operation. Another important contribution of this work is the model of the contribution of distributed energy resources in the ancillary services. In this way, a Virtual Power Player (VPP) is considered in order to aggregate, manage and interact with distributed energy resources. The VPP manages all the agents aggregated, being able to supply AS to the system operator, with the main purpose of participation in electricity market. In order to ensure their participation in the AS, the VPP should have a set of contracts with the agents that include a set of diversified and adapted rules to each kind of distributed resource. All methodologies developed and implemented in this work have been integrated into the MASCEM simulator, which is a simulator based on a multi-agent system that allows to study complex operation of electricity markets. In this way, the developed methodologies allow the simulator to cover more operation contexts of the present and future of the electricity market. In this way, this dissertation offers a huge contribution to the AS market simulation, based on models and mechanisms currently used in several real markets, as well as the introduction of innovative methodologies of market clearing process on the energy and AS joint market. This dissertation presents five case studies; each one consists of multiple scenarios. The first case study illustrates the application of AS market simulation considering several bids of market players. The energy and ancillary services joint market simulation is exposed in the second case study. In the third case study it is developed a comparison between the simulation of the joint market methodology, in which the player bids to the ancillary services is considered by network areas and a reference methodology. The fourth case study presents the simulation of joint market methodology based on Bialek topological distribution factors applied to transmission network with 7 buses managed by a TSO. The last case study presents a joint market model simulation which considers the aggregation of small players to a VPP, as well as complex contracts related to these entities. The case study comprises a distribution network with 33 buses managed by VPP, which comprises several kinds of distributed resources, such as photovoltaic, CHP, fuel cells, wind turbines, biomass, small hydro, municipal solid waste, demand response, and storage units.

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Com este trabalho pretende-se desenvolver um projeto de intervenção no âmbito da gestão do desempenho a aplicar aos responsáveis de departamento da DSV Portugal. O Sistema de Gestão de Desempenho afigura-se como um importante instrumento, estratégico para a gestão das organizações, tendo sido um enorme desafio para quem o tem implementado. Avaliar desempenhos constitui um aspeto central e uma função essencial da gestão de recursos humanos nas organizações de hoje. Ao avaliar o desempenho e o contributo dos recursos humanos para o desenvolvimento e a prossecução dos seus objetivos, a organização obtém informação que lhe permite uma tomada de decisão mais eficaz. Se os desempenhos não se encontram de acordo com o esperado, deverão ser desenvolvidas estratégias para corrigir este efeito, se o desempenho é satisfatório ou excede as expectativas, deverão os colaboradores ser premiados e valorizados. Assim, propomo-nos à criação de um projeto de intervenção numa empresa Transitária, estrategicamente alinhado com a missão, a visão, os valores e as competências valorizadas pela empresa DSV Transitários, Lda. Na elaboração deste projeto foi num primeiro momento realizada a identificação do tema junto da empresa e revisão da literatura. Foi realizado um diagnóstico interno aos procedimentos e práticas existentes, analisando assim o enquadramento organizacional onde se pretende intervir. A partir da conjugação das análises previamente indicadas e tendo por base a definição e os objetivos a que este projeto se propõem alcançar foi definido o planeamento estratégico que consta da estratégia, os objetivos estratégicos e respetivos âmbitos. Assim como foi definido o planeamento operacional, a metodologia a usar, o cronograma de atividades e momento de avaliação do projeto. Descreve-se depois a implementação, assim como os processos, procedimentos e instrumentos desenvolvidos e, finalmente realiza-se a avaliação de todo o projeto.

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In this work the mission control and supervision system developed for the ROAZ Autonomous Surface Vehicle is presented. Complexity in mission requirements coupled with flexibility lead to the design of a modular hierarchical mission control system based on hybrid systems control. Monitoring and supervision control for a vehicle such as ROAZ mission is not an easy task using tools with low complexity and yet powerful enough. A set of tools were developed to perform both on board mission control and remote planning and supervision. “ROAZ- Mission Control” was developed to be used in support to bathymetric and security missions performed in river and at seas.