Previsão de retorno de pneus inservíveis em uma cadeia de suprimentos de ciclo fechado

• Ano de defesa: 2016
• Autor(a) principal: Pereira, Marina Meireles
• Orientador(a): Machado, Ricardo Luiz
• Banca de defesa: Pires, Silvio Roberto Ignacio , Dantas, Maria José Pereira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Pontifícia Universidade Católica de Goiás
• Programa de Pós-Graduação: Programa de Pós-Graduação STRICTO SENSU em Engenharia de Produção e Sistemas
• Departamento: Engenharia
• País: BR
• Palavras-chave em Português: Cadeia de suprimentos de ciclo fechado; Previsão de retorno; Pneus inservíveis; Modelo de Função de Transferência
• Palavras-chave em Inglês: Closed-loop supply chain; Forecasting return; Scrap tires; Transfer Function Model
• Área do conhecimento CNPq: CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO
• Link de acesso: https://tede2.pucgoias.edu.br/handle/tede/2481

This research aims to apply a prediction model to a tire closed-loop supply chain to estimate the volume returned of scrap tires, through the variables that influence the amount and time that these tires are returned to destination. The methodological approach applied in this research is the modeling by applying the Transfer Function Model. It starts with the analysis that the tire closed-loop supply chain of Goiás and the Federal District is structured and there is a direct relationship between sales of tires with the amount returned. Were adopted as model input variables the amount of tires placed on the market for after-market and the size of the current fleet of these places, representing the amount of tires entered the market for new cars sold. For the output variable was considered the quantity of scrap tires collected and sent for disposal. The data for the survey were collected in the organization s databases adopted as an object of study, IBAMA, DENATRAN, ANIP and AliceWeb considering a period of 54 months. Data were analyzed by the transfer function model and the results showed that the lag time after the tires were entered on the market was around 12 months for all input variables, the return probability of the after-market are greater than the return probability of the tire fleets, and the behavior of the predicted return showed an approximate behavior of the real return with a percentage deviation of 3.4%. Therefore, this study enabled us to identify the variables that influence the return of scrap tires and scale the amount of returned volume tires and the time of this return to facilitate the planning of the tires of closed-loop supply chain.