Previsão de demanda de cargas elétricas por seleção de variáveis stepwise e redes neurais artificiais

Pós-graduação em Engenharia Elétrica - FEIS

Previsão da demanda doméstica da aviação comercial européia

This paper work has as objective the study and forecasting of the demand behavior for the European commercial aviation industry. Once economy and demand has a straight relationship, the tool chosen to perform this forecast was the Econometry. In order to get a more efficient forecast, a complete analysis of the environment in which the aviation sector is, to understand all factors with influence over the market as a whole. Only then, the variables which would be tested for the correlation with the demand were picked. The final results of this study has achieved all objectives set and has given a better view over the European Commercial Aviation Market

Previsão de demanda para peças de reposição de alto giro: aplicação de método descritivo simples comparado com o modelo suavização exponencial

O estudo de métodos de previsão de demandas é um conceito bastante popular, mas nem sempre seus resultados são facilmente aplicáveis nas organizações por várias limitações. O propósito deste artigo é apresentar um método simples e descritivo para a previsão de demanda para peças de reposição de alto giro e comparar os resultados com o modelo de suavização exponencial. Foi utilizado para isto, dados reais de consumo de uma empresa de geração de energia em dois anos com a mesma condição de contorno, e estabeleceu-se o ano de 2012 com a série de aplicação dos métodos e a série de 2013 com a série de validação dos resultados e em todas as amostras tomadas observou-se um menor erro quadrático RMSE, a favor do método descritivo simplificado. Todas as quatro séries analisadas se caracterizam pela alta dispersão dos dados, e não possuem tendências e sazonalidades.

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Modelagem auto-regressiva na previsão de demanda dos produtos de uma empresa do setor químico

Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain

Análise quantitativa de demanda em uma empresa siderúrgica

Companies, in general, operate due to the work of its subsystems and this is possible thanks to operational planning that tries to promote the best way to integrate them without giving up the mission, vision and values of the company. The main purpose of a business is to serve customers, but to be successful must take into account other factors such as survival, profitability, growth and operational standpoint to use their resources effectively. The use of tools to support the process of analysis of management decision-making is gaining importance in the context of competitiveness in the world market. The objective of this paper is to present a simulation of the process of forecasting demand to obtain optimal results for a steel company, compare the actual results with order entry and assess the magnitude of the error

Importância dos fatores não-tecnológicos na implementação do CPFR

De acordo com o Voluntary Interindustry Commerce Standards [VICS], o Collaborative Planning, Forecasting, and Replenishment [CPFR] se baseia na padronização, registro e sincronização de dados eletronicamente, apoiado pela gestão colaborativa existente entre as empresas (VICS, 2004). A partir desta definição, pode-se concluir que existem dois fatores preponderantes na implementação do CPFR: um essencialmente tecnológico e outro não-tecnológico. Nesse contexto, o propósito principal deste estudo é identificar na literatura os chamados fatores não tecnológicos que envolvem o CPFR e analisá-los em situações reais. A importância desses fatores é analisada, então, por meio do estudo de dois casos reais de implementação do CPFR, respectivamente, em uma grande rede de fast food e em um grande distribuidor de alimentos, que operam no Brasil. Os resultados destacam, principalmente, que a previsão da demanda realizada pela empresa coordenadora do CPFR é preponderante sobre o entendimento da demanda por todos os elos da cadeia de suprimentos, que a cultura colaborativa é considerada muito importante no relacionamento ao longo da cadeia (embora não seja determinante para a implementação dos processos) e que o monitoramento das atividades é fundamental para o alinhamento das empresas na gestão do CPFR.

A gestão de estoques em sistemas produtivos Engineering-To-Order e Make-To-Stock: estudo de casos em empresas do setor gráfico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Melhoria do planejamento para o fornecimento de materiais de modificações em aeronaves executivas

This paper presents a material demand forecasting to executive aircrafts modifications, the objective was to determinate a cadence of kits of materials in order reduce over stock, but also keeping the customer quality support. This work was motivated by the strong tendency that the market has to cut costs, especially those that do not add value to the product, waste. To solve the problem the Poisson probability distribution was used and also the error measures MPE, MAPE and MSE. At the end, after some adjustments, we found a satisfactory model for the problem

Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

The influence of the alveolar ridge shape on the stress distribution in a free-end saddle removable partial denture supported by implant

The alveolar ridge shape plays an important role in predicting the demand on the support tooth and alveolar bone in the removable partial denture (RPD) treatment. However, these data are unclear when the RPD is associated with implants. This study evaluated the influence of the alveolar ridge shape on the stress distribution of a free-end saddle RPD partially supported by implant using 2-dimensioanl finite element analysis (FEA). Four mathematical models (M) of a mandibular hemiarch simulating various alveolar ridge shapes (1-distal desceding, 2- concave, 3-horizontal and 4-distal ascending) were built. Tooth 33 was placed as the abutment. Two RPDs, one supported by tooth and fibromucosa (MB) and other one supported by tooth and implant (MC) were simulated. MA was the control (no RPD). The load (50N) were applied simultaneously on each cusp. Appropriate boundary conditions were assigned on the border of alveolar bone. Ansys 10.0 software was used to calculate the stress fields and the von Mises equivalent stress criteria (σvM) was applied to analyze the results. The distal ascending shape showed the highest σvM for cortical and medullar bone. The alveolar ridge shape had little effect on changing the σvM based on the same prosthesis, mainly around the abutment tooth.

Aplicações de sistemas multiagentes na previsão espacial de demanda elétrica em sistemas de distribuição

Pós-graduação em Engenharia Elétrica - FEIS

Previsão espacial de demanda em sistemas de distribuição com uma base reduzida de dados

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Previsão de carga multinodal utilizando redes neurais de regressão generalizada

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Previsão de cargas elétricas através de um modelo híbrido de regressão com redes neurais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)