Mostrando 5 resultados de: 5
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2017 IEEE 3rd Colombian Conference on Automatic Control, CCAC 2017 - Conference Proceedings(1)
Chemical Engineering Transactions(1)
Drying Technology(1)
IFAC-PapersOnLine(1)
International Journal of Production Research(1)
Área de conocimiento
Ingeniería de manufactura(2)
Innovación(2)
Inteligencia artificial(2)
Aprendizaje automático(1)
Energía(1)
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scopus(5)
Assistant: Learning and robust decision support system for agile manufacturing environments
Conference ObjectAbstract: The European project ASSISTANT will provide a set of AI-based digital twins that helps process enginPalabras claves:Artificial Intelligence, data analytics, Decision aid, Digital twins, Process and production planning, Real-time control, reconfigurable manufacturing systems, schedulingAutores:Beldiceanu N., Dolgui A., Eduardo Vyhmeister, Gonnermann C., Gonzalez-Castañé G., Kousi N., Meyers B., Östberg P.O., Prud'homme J., Thevenin S.Fuentes:scopusControlled high pressure grinding roll by model pbkp_redictive control
Conference ObjectAbstract: High Pressure Grinding Rolls (HPGR) technology has been considered as an alternative in the mining iPalabras claves:Dynamic modelling, HPGR, MPC, SimulationAutores:Eduardo Vyhmeister, Fernando Cepeda Vaca, Guerra C.F., Marcelo V. Garcia, Reyes-Bozo L., Rosa Galleguillos-Pozo, Valdes-Gonzalez H.Fuentes:scopusNeural Networks and Support Vector Machine models applied to energy consumption optimization in semiautogeneous grinding
Conference ObjectAbstract: Semiautogenous (SAG) mills for ore grinding are large energy consumption equipments. The SAG energyPalabras claves:Autores:Acuña G., Cubillos F.A., Curilem M., Eduardo VyhmeisterFuentes:scopusRotary dryer control using a Grey-Box Neural Model scheme
ArticleAbstract: The application of a Grey-box Neural Model (GNM) in a nonlinear model pbkp_redictive control schemePalabras claves:Dryer control, Drying modeling, Nonlinear model pbkp_redictive controlAutores:Acuña G., Alvarez P., Cubillos F.A., Eduardo VyhmeisterFuentes:scopusThe ASSISTANT project: AI for high level decisions in manufacturing
ArticleAbstract: This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSIonPalabras claves:Artificial Intelligence, data analytics, Digital twins, Process and production planning, reconfigurable manufacturing systems, scheduling and real-time controlAutores:Castane G.G., Dolgui A., Eduardo Vyhmeister, Kousi N., Meyers B., Östberg P.O., Thevenin S.Fuentes:scopus