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

Proposta de metodologia para gestão de produção, visando redução no consumo de energia elétrica em uma unidade fabril do setor de bens de consumo

Actually the energy efficiency is making more space in the industry, due to the search for the sustainability, the electrical energy costs reduction, the goals achievement or the efficiency of production processes. In consumer goods industries, such a beverage industry, as the work is based, the productivity is directly related to the electrical energy consumption. The development of methodologies and/or routines, in addition to some tools which allow to align more efficiently these two aspects (production and consumption of electrical energy), in the viewpoint of the Energy Conservation, is very important. In this case, the study will show the Plant Modulation concepts, a production management methodology, based in some factors related to the productive process, installed equipment, production supplies and energy cost. The proposed methodology was implanted in a plant along 2015 and show the results, in face to confirm its efficiency. Finally, in this study, it was shown the capacity of Plant Modulation to positively impact in the energy efficiency inside a big industry

Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow