Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Caridá, Vinicius Fernandes
Orientador(a): Morandin Júnior, Orides lattes
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
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 Ciência da Computação - PPGCC
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7985
Resumo: In recent years, manufacturers are increasingly applying automation techniques with the aim of increase their efficiency to remain competitive. The material handling is an essential activity in any process of production and its effectiveness has severe impacts on production costs. Systems of automated guided vehicles (AGVs) have become an important strategic tool for factories and automated warehouses. In a very competitive business scenario, they can increase productivity and reduce costs. The management of these AGVs is the key to a transport system that ensures the improvements envisioned by the industry. One of the main problems encountered in the management of AGVs is the dispatch decision. This paper proposes a vehicles dispatch model based on a fuzzy cascade system for consideration of multiple attributes of the factory and a structure based on state space that enables the extraction of information of future states of the industrial production system. The objective is to reduce makespan and tardiness values of the production system. Two factory scenarios are simulated and tests are performed of the model and five other methods of dispatch. A statistical validation is realized of the results in which corroborates with 97% confidence the hypotheses of the work.