Marcelino Rivas
Marcelino Rivas
Universidad de Matanzas
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Cited by
Cited by
Genetic algorithm-based multi-objective optimization of cutting parameters in turning processes
RQ Sardinas, MR Santana, EA Brindis
Engineering Applications of Artificial Intelligence 19 (2), 127-133, 2006
Automatic selection of optimal parameters based on simple soft-computing methods: a case study of micromilling processes
I la Fé-Perdomo, G Beruvides, R Quiza, R Haber, M Rivas
IEEE Transactions on Industrial Informatics 15 (2), 800-811, 2018
Computer vision system for welding inspection of liquefied petroleum gas pressure vessels based on combined digital image processing and deep learning techniques
YJ Cruz, M Rivas, R Quiza, G Beruvides, RE Haber
Sensors 20 (16), 4505, 2020
Ensemble of convolutional neural networks based on an evolutionary algorithm applied to an industrial welding process
YJ Cruz, M Rivas, R Quiza, A Villalonga, RE Haber, G Beruvides
Computers in Industry 133, 103530, 2021
Online detection of run out in microdrilling of tungsten and titanium alloys
G Beruvides, R Quiza, M Rivas, F Castaño, RE Haber
The International Journal of Advanced Manufacturing Technology 74, 1567-1575, 2014
Sustainability-focused multi-objective optimization of a turning process
I La Fé Perdomo, R Quiza, D Haeseldonckx, M Rivas
International Journal of Precision Engineering and Manufacturing-Green …, 2020
Optimización Multiobjetivos del proceso de Torneado
R Quiza
Director: Marcelino Rivas Santanas. Tesis Doctoral, Universidad de Matanzas …, 2004
Surface roughness Ra prediction in Selective Laser Melting of 316L stainless steel by means of artificial intelligence inference
I La Fé-Perdomo, J Ramos-Grez, R Mujica, M Rivas
Journal of King Saud University-Engineering Sciences, 2021
Towards sustainability of manufacturing processes by multiobjective optimization: A case study on a submerged arc welding process
D Rivas, R Quiza, M Rivas, RE Haber
IEEE Access 8, 212904-212916, 2020
A two-step machine learning approach for dynamic model selection: A case study on a micro milling process
YJ Cruz, M Rivas, R Quiza, RE Haber, F Castaño, A Villalonga
Computers in Industry 143, 103764, 2022
Optimization of the cutting regime in the turning of the AISI 316L steel for biomedical purposes based on the initial progression of tool wear
R del Risco-Alfonso, R Pérez-Rodríguez, PC Zambrano Robledo, ...
Metals 11 (11), 1698, 2021
Hybrid modelling and optimization of the oblique cutting of AISI 1045 steel
ILF Perdomo, R Quiza, M Rivas, V Ramtahalsing
International Journal of Manufacturing, Materials, and Mechanical …, 2018
Artificial intelligence-based modelling and optimization of microdrilling processes
G Beruvides, F Castaño, RE Haber, R Quiza, M Rivas
2014 IEEE Symposium on Computational Intelligence for Engineering Solutions …, 2014
A fuzzy-genetic system to predict the cutting force in microdrilling processes
G Beruvides, R Quiza, M Rivas, F Castaño, RE Haber
IECON 2014-40th Annual Conference of the IEEE Industrial Electronics Society …, 2014
Optimización del Uso del NaSH en la Flotación de Minerales de Cobre
M Bosse, V Conejeros, M RIVAS
Universidad Católica del Norte, Chile, 2009
Optimización del torneado multipasada para producciones sostenibles utilizando algoritmos genéticos y enjambre de partículas
IL Fé-Perdomo, R Quiza, M Rivas-Santana
Dyna 85 (204), 59-64, 2018
Intelligent models for predicting the thrust force and perpendicular vibrations in microdrilling processes
G Beruvides, F Castaño, RE Haber, R Quiza, M Rivas
2014 IEEE 26th international conference on tools with artificial …, 2014
Thermal and morphological characterization of 3D-printed PLA scaffolds for biomedical applications
A González González, M Rivas Santana, PC Zambrano Robledo, R Quiza
MRS Advances 7 (35), 1206-1211, 2022
Optimización multiobjetivo de la soldadura automática bajo fundente del acero JIS 3116
L Fé-Perdomo, M Rivas-Santana, R Quiza-Sardiñas, ...
Ingeniería Mecánica 20 (2), 77-82, 2017
Influencia de los modelos de fricción en la simulación por elementos finitos del microfresado de Ti6Al4V
ILF Perdomo, CC Díaz, MR Santana, R Quiza
Revista Iberoamericana de Ingeniería Mecánica 21 (2), 21-30, 2017
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