Multi-agent system for steel manufacturing process
This work was carried out in the company ACINOX Las Tunas, Cuba, to design an integrated automation architecture based on intelligent agents for control, monitoring, and decision-making in the production process that guarantees an improvement in planning and management of the process in the steelwor...
- Autores:
-
Ricardo Rodríguez, Angel Raúl
Benítez, Israel F
González Yero, Guillermo
Núñez Alvarez, José Ricardo
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2022
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/9047
- Acceso en línea:
- https://hdl.handle.net/11323/9047
https://repositorio.cuc.edu.co/
- Palabra clave:
- Agents
Artificial intelligence
Decision support systems
Integrated manufacturing
Intelligent control
- Rights
- openAccess
- License
- Atribución-CompartirIgual 4.0 Internacional (CC BY-SA 4.0)
Summary: | This work was carried out in the company ACINOX Las Tunas, Cuba, to design an integrated automation architecture based on intelligent agents for control, monitoring, and decision-making in the production process that guarantees an improvement in planning and management of the process in the steelwork plant. The great differences of technologies and systems of each steel mill and the multiple restrictions, methods, and techniques, within a wide dynamic strongly concatenated, do not generalize automation systems feasibly. In our research, we use international research results and the experience of the plant technologists to create three levels of distributed intelligent architecture: business, production planning-control, and steel manufacturing. Each level manages to integrate and balance the particular and general interests for efficient decision-making combined between hierarchy and heterarchy in this steelwork plant, which will be reflected in a reduction of at least 99% of the time used for decision-making concerning the current system, which can lead to a decrease in refractory costs, energy consumption, and production cost. The effectiveness of the solution is demonstrated with scenario validation and expert evaluation. |
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