Sistema de apoio à decisão na localização de peças

A globalização, nas suas diversas dimensões, está a tornar o mundo cada vez mais pequeno, alterando as nossas vidas e transformando a forma como as empresas fazem negócios. Estamos cada vez mais expostos aos traços e práticas das outras culturas à medida que a tecnologia diminui os custos da comunicação global e das viagens. A globalização está a obrigar as empresas a serem mais competitivas ao mesmo tempo que os países reduzem as barreiras ao comércio internacional e ao investimento estrangeiro. A competitividade das empresas obriga-as a serem mais eficientes e eficazes, logo a pensarem os seus processos internos de forma a procurarem a sua otimização e melhorarem a sua produtividade, com a notória consequência na satisfação do cliente. Para a satisfação do cliente é necessário que as operações dentro do sistema de distribuição, nomeadamente as realizadas no armazém, sejam otimizadas. Esta otimização é atingida quando as encomendas dos clientes estiverem completas e prontas a serem despachadas em tempo útil e todos os processos necessários para o efeito tenham ocorrido no menor espaço de tempo possível e com o mínimo de recursos. O planeamento das operações no armazém tem de determinar o tempo e a ordem das operações bem como os recursos necessários de forma a não acontecerem congestionamentos. A Caetano Parts, uma empresa de revenda de peças de substituição automóvel, identificou um congestionamento na localização de peças que chegavam pela primeira vez ao seu armazém, o que suscitou a necessidade do desenvolvimento de uma ferramenta que permitisse proceder à localização destas peças de uma forma mais expedita, permitindo ganhos significativos de tempo na arrumação das peças e consequentemente no tempo gasto na sua procura/separação e posterior envio para os clientes. A ferramenta desenvolvida consiste num programa em Visual Basic for Applications (VBA) cuja conceção, desenvolvimento e descrição das funcionalidades serão abordados ao longo do trabalho. Os testes realizados ao longo do desenvolvimento validaram o correto funcionamento da ferramenta.

Computational intelligence applications for future power systems

Power system planning, control and operation require an adequate use of existing resources as to increase system efficiency. The use of optimal solutions in power systems allows huge savings stressing the need of adequate optimization and control methods. These must be able to solve the envisaged optimization problems in time scales compatible with operational requirements. Power systems are complex, uncertain and changing environments that make the use of traditional optimization methodologies impracticable in most real situations. Computational intelligence methods present good characteristics to address this kind of problems and have already proved to be efficient for very diverse power system optimization problems. Evolutionary computation, fuzzy systems, swarm intelligence, artificial immune systems, neural networks, and hybrid approaches are presently seen as the most adequate methodologies to address several planning, control and operation problems in power systems. Future power systems, with intensive use of distributed generation and electricity market liberalization increase power systems complexity and bring huge challenges to the forefront of the power industry. Decentralized intelligence and decision making requires more effective optimization and control techniques techniques so that the involved players can make the most adequate use of existing resources in the new context. The application of computational intelligence methods to deal with several problems of future power systems is presented in this chapter. Four different applications are presented to illustrate the promises of computational intelligence, and illustrate their potentials.

Rapid determination of tartaric acid in wines

A flow-spectrophotometric method is proposed for the routine determination of tartaric acid in wines. The reaction between tartaric acid and vanadate in acetic media is carried out in flowing conditions and the subsequent colored complex is monitored at 475 nm. The stability of the complex and the corresponding formation constant are presented. The effect of wavelength and pH was evaluated by batch experiments. The selected conditions were transposed to a flowinjection analytical system. Optimization of several flow parameters such as reactor lengths, flow-rate and injection volume was carried out. Using optimized conditions, a linear behavior was observed up to 1000 µg mL-1 tartaric acid, with a molar extinction coefficient of 450 L mg-1 cm-1 and ± 1 % repeatability. Sample throughput was 25 samples per hour. The flow-spectrophotometric method was satisfactorily applied to the quantification of tartaric acid (TA) in wines from different sources. Its accuracy was confirmed by statistical comparison to the conventional Rebelein procedure and to a certified analytical method carried out in a routine laboratory.

Simulação da qualidade da água em parte de ao Grande Porto

Este trabalho tem como objetivo a modelação hidráulica e de qualidade de água de parte de uma rede de distribuição a alta pressão do grande Porto. Após calibração de um modelo utilizado no software EPANet foi possível simular o decaimento do cloro livre num troço da rede de abastecimento. Foi ainda possível concluir que os valores dos parâmetros característicos do modelo de qualidade são uma constante de decaimento no seio do fluido de 1,78 dia-1 (0,001239 min-1) a cerca de 22 ºC e, no ramal 6244-6245 Ramalde – Cabanas – Pedrouços, uma constante de decaimento na parede da tubagem de forma generalizada de 0,28 m/dia. Não foi possível obter conclusões sobre a adutora 6261 Jovim-Nova Sintra 2, ficando explícita a necessidade de um maior controlo sobre a variável temperatura.

Otimização da atividade de picking num armazém de peças – um caso de estudo

Mestrado em Engenharia Mecânica – Gestão Industrial

Smart meters as a tool for energy efficiency

Gradually smart grids and smart meters are closer to the home consumers. Several countries has developed studies focused in the impacts arising from the introduction of these technologies and one of the main advantages are related to energy efficiency, observed through the awareness of the population on behalf of a more efficient consumption. These benefits are felt directly by consumers through the savings on electricity bills and also by the concessionaires through the minimization of losses in transmission and distribution, system stability, smaller loading during peak hours, among others. In this article two projects that demonstrate the potential energy savings through smart meters and smart grids are presented. The first performed in Korea, focusing on the installation of smart meters and the impact of use of user interfaces. The second performed in Portugal, focusing on the control of loads in a residence with distributed generation.

Desenvolvimento do processo de produção de peça plástica revestida a PVC para a indústria automóvel

O desenvolvimento do processo de produção de um produto para a indústria automóvel é sempre um desafio de nível de dificuldade exigente. Este trabalho teve por base o estudo do desenvolvimento do processo de produção de um produto para a área automóvel, constituído por diversos componentes e exigindo diversas etapas de produção. O desafio partiu de um cliente da SIMOLDES - PLÁSTICOS, S.A. que necessitava de uma peça em plástico para um novo modelo de automóvel. Foram estabelecidas as condições iniciais impostas pelo cliente e foram estudados os condicionalismos impostos pelas mesmas. Foram estudadas diferentes alternativas com vista à optimização do processo, garantindo a qualidade e tentando minimizar o custo final do produto. Foi realizada uma optimização dos moldes, por forma a poderem ser utilizadas máquinas com Força de Fecho mais baixa. Foram desenvolvidos alguns equipamentos que permitiram à empresa optar por novas formas de produção, utilizando materiais mais amigos do ambiente. Foram estudadas as condições de distribuição e optimização das tarefas, com vista à garantia do cumprimento dos prazos de entrega exigidos pelo cliente. Foi estudado o ‘layout’ que optimizou as operações de transporte das diferentes peças que constituem o produto final. Este trabalho foi elaborado com base num trabalho desenvolvido e implementado na SIMOLDES – PLÁSTICOS, S.A.

Experimental study on the impact of using a fan coil in the evaluation of contaminant removal effectiveness of common air diffusion strategies

Indoor Air 2016 - The 14th International Conference Indoor Air Quality and Climate

Study of distribution network demand response events in the Portuguese system

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. Grid operators and utilities are taking new initiatives, recognizing the value of demand response for grid reliability and for the enhancement of organized spot markets’ efficiency. This paper proposes a methodology for the selection of the consumers that participate in an event, which is the responsibility of the Portuguese transmission network operator. The proposed method is intended to be applied in the interruptibility service implemented in Portugal, in convergence with Spain, in the context of the Iberian electricity market. This method is based on the calculation of locational marginal prices (LMP) which are used to support the decision concerning the consumers to be schedule for participation. The proposed method has been computationally implemented and its application is illustrated in this paper using a 937 bus distribution network with more than 20,000 consumers.

Combined heat and power and consumption optimization in a SCADA-based system

The operation of power systems in a Smart Grid (SG) context brings new opportunities to consumers as active players, in order to fully reach the SG advantages. In this context, concepts as smart homes or smart buildings are promising approaches to perform the optimization of the consumption, while reducing the electricity costs. This paper proposes an intelligent methodology to support the consumption optimization of an industrial consumer, which has a Combined Heat and Power (CHP) facility. A SCADA (Supervisory Control and Data Acquisition) system developed by the authors is used to support the implementation of the proposed methodology. An optimization algorithm implemented in the system in order to perform the determination of the optimal consumption and CHP levels in each instant, according to the Demand Response (DR) opportunities. The paper includes a case study with several scenarios of consumption and heat demand in the context of a DR event which specifies a maximum demand level for the consumer.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.

Finite Element Analysis (FEA) applied to heat transfer optimization process of pultrusion die systems

The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.