Análise de capacidade de médio prazo com formação de células de manufatura: uma modelagem em empresa de usinagem aeroespacial

• Ano de defesa: 2023
• Autor(a) principal: Lima, Rodrigo Franco de
• Orientador(a): Sagawa, Juliana Keiko
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• Palavras-chave em Português: Manufatura celular; Análise de grupo; Programação da produção; Production scheduling; Sistema de produção conforme pedido; Setor aeroespacial; Otimização; Capacidade
• Palavras-chave em Inglês: Cellular manufacturing; Group analysis; Make-to-Order; Aerospace sector; Optimization; Capacity
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO; ENGENHARIAS::ENGENHARIA DE PRODUCAO::PESQUISA OPERACIONAL
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/19342

The production environment characteristic of the aerospace machining sector is the Make-to-Order, with the manufacture of small and medium production batches. Given the possibility of variation in demand, whether in volume or variety, the production system must be responsive and attend the performance targets in terms of cost, quality and time. This flexibility of production environments increases the complexity of decisions, especially in those environments that operate under high variation in the product mix and reduced delivery times. Proper production scheduling directly influences production performance goals and has a great impact on customer service performance. The work aims at the development of a system using a mixed integer programming model and a post-processing interface for temporary cell formation and orders’ allocation, considering the demand of final customer of a given period, and aiming at an optimized use of capacity in the medium term. The model is based on a real case of an aerospace machining company, and contributes to the adequate use of manufacturing resources, to an accurate decision making based on the presented scenario and to the improvement of customer service performance. The differential of the proposed model, in relation to the existing models in the literature, is the fact that it was developed considering a real manufacturing environment (empirical study), with the search for the best formation and reconfiguration of the cell considering the demand, the productive capacity and the machine setup, through the minimization of three objectives in just one model: backlog of orders, non-use of the machine by the route allocated in the cell and intercellular movement. In prior literature, hypothetical systems are modelled, and the cell formation and order allocation are done in two steps, instead of simultaneously, as in the proposed model. The management analysis of the solution obtained, in terms of load and product flows between the machines, made it possible to identify bottlenecks and idleness and possibilities for technological changes in the processes, to better meet demand and balance loads. The work will also result in a technological product for the studied company.