Statistical analysis of models of the demand forecast-case study on sale cardboard for recycling

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Data

2009-01-01

Autores

Da Silva, Nilza Regina [UNESP]
Esguícero, Fabio José [UNESP]
Da Silva, Antonio Carlos Dalácqua
Leão, Alcides L. [UNESP]
Esperancini, Maura Seiko Tsutsui [UNESP]

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Resumo

The activity of cardboard recycling when correctly planned and organized, offers great possibilities of economic profits for the enterprising agent, beyond social and environmental benefits, as the job creation and economy of raw material. With the increment of the activity of outnumber recycling initiatives of associations or cooperatives of sorting are observed which collect and commercialize cardboard and other materials, in order to supply its increasing demand. As example of these initiatives, it is distinguished the Association of people which collect garbage in the city of São Manuel, São Paulo, Brazil (ACAPEL), that monthly separates and collects about 38,000 kg of recyclable materials. To stock the materials it is necessary to know the demand of the cardboard, making possible to the integrants of the association, information that make possible that they correctly take decisions in function of the forecast of the demand of its products. The objective of this study is to find tools to make the statistical forecasts of demand, which is adequate to the historical data of commercialization of the ACAPEL. This model will supply coherent answers with the objective of the planning in short and long term sales. In this study, in accordance with the existing theories, it used four quantitative models of analysis of forecast of sale of its products in order to compare itself with the real demand. In the case of the ACAPEL, in the years 2003 through 2007, the best method of demand forecast is the mobile exponential average that presented low absolute medium detour in relation to the foreseen values and effective demand.

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Cardboard, Demand, Prevision, Recycling

Como citar

ECOS 2009 - 22nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, p. 1087-1094.