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...

Full description

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)
Description
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.