Resolução do problema de sequenciamento de múltiplas linhas de montagem de modelos mistos em ambiente de produção enxuta

• Autor(a) principal: Ushizima, Mariana Monteiro [UNESP]
• Data de Publicação: 2014
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://hdl.handle.net/11449/123034; http://www.athena.biblioteca.unesp.br/exlibris/bd/capelo/2015-05-04/000811659.pdf
• topic: Metodos de linha de montagem; Produção enxuta; Engenharia de produção; Metodos de simulação; Lean manufacturing

This work deals with the sequencing of Multi-Mixed-Model Assembly Lines in a lean manufacturing environment, where an operational structure where several kanbans support several mixed-model assembly lines, so that all assembly lines can receive parts or sub-assemblies from all suppliers. To optimize this system, the sequencing seeks to minimize the distance between the real consumption and the constant ideal consumption of parts or subassemblies, thereby reducing the scaling of kanbans and intermediate stocks. To solve the sequencing problems, the method Clustering Search was applied along with the metaheuristics Variable Neighborhood Search, Simulation Annealing and Iterative Local Search. Instances from the literature and generated instances were tested, thus allowing comparing the methods to each other and with other methods presented in the literature. The performance of the Clustering Search with Iterated Local Search stands out by the quality and robustness of their solutions, and mainly for its efficiency, whereas it converges to better results at a lower computational cost