Consumption Electrical Energy Forecast for a Automotive Paint Shop

• Autor(a) principal: Oliveira, Rafael Barbosa de
• Data de Publicação: 2023
• Outros Autores: Couto de Lima Souza, Paulo Henrique, Silva, Thiago Cavalcanti, Kirschner, Victor Ernesto Santos, Lorenzato, Fausto, Maciel, Alexandre M.A.
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Revista de Engenharia e Pesquisa Aplicada
• Texto Completo: http://revistas.poli.br/index.php/repa/article/view/2780

This article aims to predict the consumption behavior of electrical energy in a Paint Shop of a typical automotive industry by the usage of time series. From the data and it's relationship taken from the installed machines it will be used data science tools to correlate and predict it's consumption and even to model the next time series. The analysis will covers from an initial understanding of the data to it’s implementation in predictive models for future time series. It will focus on advanced applications in order to achieve valuable insights of energy consumption pattern. It will also consider the machinery complexes iterations. Deep understanding of those relationships will provide a better base for accurate models. Finally it will allow a much efficient consumption energy management for a Paint Shop.