Detalhes bibliográficos
| Ano de defesa: |
2006 |
| Autor(a) principal: |
Roman, Eros Schettini |
| Orientador(a): |
Morandin Júnior, Orides
 |
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de São Carlos
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Ciência da Computação - PPGCC
|
| Departamento: |
Não Informado pela instituição
|
| País: |
BR
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
https://repositorio.ufscar.br/handle/20.500.14289/426
|
Resumo: |
The production sequencing is an area of great importance in Production Planning and Control, because businesses are looking for higher productivity and competitivity, in order to meet the demands and expectations of their respective markets. To hasten and to be flexible the production processes through efficient production sequencing contributes to satisfy this market. Simulation technologies have been used to model, plan and control complex manufacturing systems. To accomplish the production sequencing in these environments, with the support of the simulation, it is necessary to reduce the total amount of simulated scenarios and evaluate the simulation results. Artificial Intelligence techniques can help these tasks. This work has proposed an intelligent system for production sequencing, supported by simulation techniques and Artificial Intelligence. This goal is based on ideas already studied in the research group of the Computer Science Department at Federal University of São Carlos. The system was implanted and many tests were accomplished. First, some sequences are selected with products that are able to enter the production system. Then the sequences are simulated and, forward, put on action an estimate process that classifies them. To run the tests was considered a specific Flexible Manufacturing System (FMS). |
