Alvarado-Hernandez, A. I., Checa D., Osornio-Rios R.A., Bustillo A., and Antonino Daviu J.A., A Virtual Reality Environment Based on Infrared Thermography for the Detection of Multiple Faults in Kinematic Chains, Electronics, 2024, 13, no. 13: 2447. https://doi.org/10.3390/electronics13132447
Rodriguez-Garcia, B.; Ramírez-Sanz, J.M.; Miguel-Alonso, I.; Bustillo, A. Enhancing Learning of 3D Model Unwrapping through Virtual Reality Serious Game: Design and Usability Validation. Electronics 2024, 13, 1972. https://doi.org/10.3390/electronics13101972
Rodriguez-Garcia, B., Guillen-Sanz, H., Checa, D. Bustillo. A. A systematic review of virtual 3D reconstructions of Cultural Heritage in immersive Virtual Reality. Multimedia Tools and Applications (2024). https://doi.org/10.1007/s11042-024-18700-3
Maestro-Prieto, J., Ramírez-Sanz, J., Bustillo, A., J.J. Rodríguez. Semi-supervised diagnosis of wind-turbine gearbox misalignment and imbalance faults. Applied Intelligence (2024). https://doi.org/10.1007/s10489-024-05373-6
Guillen-Sanz, H., Checa, D., Miguel-Alonso, I. Bustillo, A. A systematic review of wearable biosensor usage in immersive virtual reality experiences. Virtual Reality 28, 74 (2024).
Miguel-Alonso, I., Checa, D., Guillen-Sanz, H. Bustillo A., Evaluation of the novelty effect in immersive Virtual Reality learning experiences. Virtual Reality 28, 27 (2024). https://doi.org/10.1007/s10055-023-00926-5
Ramírez-Sanz, J.M., Maestro-Prieto J.A., Arnaiz-González A., Bustillo A., Semi-supervised learning for industrial fault detection and diagnosis: A systemic review, ISA Transactions 143 (2023) 255–270, https://doi.org/10.1016/j.isatra.2023.09.027.
Pimenov D.Y., Bustillo A., Wojciechowski S., Sharma V.S., Gupta M.K., Kuntoğlu M., Artificial Intelligence Systems for Tool Condition Monitoring in Machining: Analysis and Critical Review, Journal of Intelligent Manufacturing (2023) 34:2079–2121. https://doi.org/10.1007/s10845-022-01923-2
Martinez, K.; Checa, D.; Bustillo, A. Development of the Engagement Playability and User eXperience (EPUX) Metric for 2D-Screen and VR Serious Games: A Case-Study Validation of Hellblade: Senua’s Sacrifice. Electronics 2024, 13, 281.
Romero P.E., Barrios J.M., Molero E., Bustillo A., Tuning 3D-printing parameters to produce vertical ultra-hydrophobic PETG parts with low ice adhesion: A food industry case study, Proc IMechE Part B: J Engineering Manufacture, 2024;238(5):750-758, DOI: 10.1177/09544054231178.
Checa, G. Urbikain, A. Beranoagirre, A. Bustillo, L. N. López de Lacalle, Using Machine-Learning techniques and Virtual Reality to design cutting tools for energy optimization in milling operations, International Journal of Computer Integrated Manufacturing (2022), 1-21, doi: 10.1080/0951192X.2022.2027020
Checa, I. Miguel-Alonso, A. Bustillo, Immersive virtual-reality computer-assembly serious game to enhance autonomous learning, Virtual Reality (2023) 27:3301–3318. DOI: 10.1007/s10055-021-00607-1
Miguel-Alonso, I.; Rodriguez-Garcia, B.; Checa, D.; Bustillo, A. Countering the Novelty Effect: A Tutorial for Immersive Virtual Reality Learning Environments. Appl. Sci. 2023, 13, 593. https://doi.org/10.3390/app13010593
Checa, J. J. Saucedo-Dorantes, R. A. Osornio-Rios, J. A. Antonino-Daviu, A. Bustillo, Virtual Reality Training Application for the Condition-Based Maintenance of Induction Motors. Applied Science, 2022, 12, 414.
Martinez,,K., M. I. Menéndez-Menéndez, and A. Bustillo. 2022. A New Measure for Serious Games Evaluation: Gaming Educational Balanced (GEB) Model, Applied Sciences 12, no. 22: 11757. https://doi.org/10.3390/app122211757
Martinez, M. I. Menéndez-Menéndez, A. Bustillo, A systematic review of serious games for children and adolescents: awareness, prevention, detection and therapy for depression and anxiety. JMIR Serious Games. 9(4), 2021, Oct-Dec. e30482, 1-19 doi: 10.2196/30482.
Checa, K. Martínez, R. A. Osornio-Rios, A. Bustillo, Virtual Reality opportunities in the reduction of occupational hazards in industry 4.0. DYNA, 2021, 96(6), 620-626.
Cerro, P. E. Romero, O. Yigit, A. Bustillo, Use of machine learning algorithms for surface roughness prediction of printed parts in polyvinyl butyral via fused deposition modeling, The International Journal of Advanced Manufacturing Technology, 2021, 115, 2465-2475.
Bustillo, D.Y. Pimenov, M. Mia, W. Kaplonek, Machine-learning for automatic prediction of flatness deviation considering the wear of the face mill teeth. Journal of Intelligent Manufacturing, 2021, 32, 895-912.
Bustillo, R. Reis, A.R. Machado, D.Y. Pimenov, Improving the accuracy of machine-learning models with data from machine test repetitions. Journal of Intelligent Manufacturing, 2022, 33(1), 203-221.
Diez-Pastor J.F., A. Gil Del Val, F. Veiga, A. Bustillo, High-accuracy classification of thread quality in tapping processes with ensembles of classifiers for imbalanced learning, Measurement, 2021, 168,108328.
Checa, A. Bustillo, A review of immersive virtual reality serious games to enhance learning and training, Multimedia Tools and Applications, 2020, 79(9), 5501-5527.
Checa, A. Bustillo, Advantages and limits of virtual reality in learning processes: Briviesca in the fifteenth century, Virtual Reality London, 2020, 24(1), 151-161.
Juez-Gil, I. N. Erdakov, A. Bustillo, D. Y. Pimenov, A regression-tree multilayer-perceptron hybrid strategy for the prediction of ore crushing-plate lifetimes, Journal of Advanced Research, 2019, 18, 173-184
Beranoagirre , G. Urbikain, R. Marticorena, A. Bustillo, L. N. Lopez de Lacalle, Sensitivity Analysis of Tool Wear in Drilling of Titanium Aluminides, Metals, 2019, 9(3), 297.
Y. Pimenov, A. Hassui, S. Wojciechowski, M. Mia, A. Magri, D. I. Suyama, A. Bustillo, G. Krolczykand, M. K. Gupta, Effect of the Relative Position of the Face Milling Tool towards the Workpiece on Machined Surface Roughness and Milling Dynamics, Applied Science, 2019, 9(5), 842.
Checa, J. Zulaika, I. Lazkanotegi, A. Bustillo, Machining optimization of large casting components by remote monitoring and 3D visualization techniques, Dyna, 2018, 93(6), 668-674.
Bustillo, G. Urbikain, J. M. Perez, O. M. Pereira, L. N. Lopez de Lacalle, Smart optimization of a friction-drilling process based on boosting ensembles, Journal of Manufacturing Systems, 2018, 48, 108-121.
Oleaga, C. Pardo, J. J. Zulaika, A. Bustillo, A machine-learning based solution for chatter prediction in heavy-duty milling machines, Measurement, 2018, 128, 34-44.
Bustillo, D.Yu. Pimenov, M. Matuszewski, T. Mikolajczyk, Using artificial intelligence models for the prediction of surface wear based on surface isotropy levels, Robotics and Computer-Integrated Manufacturing 2018, 53, 215-227.
Grzenda, A. Bustillo, Semi-supervised roughness prediction with partly unlabeled vibration data streams, Journal of Intelligent Manufacturing 2019, 30, 933-945.
D.Y. Pimenov, A. Bustillo, T. Mikolajczyk, Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth, Journal of Intelligent Manufacturing, 2018 29(5), 1045-1061.
Santos, J. Maudes, A. Bustillo, Identifying maximum imbalance in datasets for fault diagnosis of Gearboxes, Journal of Intelligent Manufacturing, 2018, 29(2), 333-351.
Mikolajczyk, H. Fuwen, L. Moldovan, A. Bustillo, M. Matuszewski, K. Nowicki, Selection of machining parameters with Android application made using MIT App Inventor bookmarks, Procedia Manufacturing, 2018, 22, 172-179.
Mikoajczyk, K. Nowicki, A. Bustillo, D. Yu Pimenov, Predicting tool life in turning operations using neural networks and image processing, Mechanical Systems and Signal Processing, 2018, 104, 503-513.
Maudes, A. Bustillo, A.J. Guerra, J. Ciurana, Random Forest ensemble prediction of stent dimensions in microfabrication processes, The International Journal of Advanced Manufacturing Technology, 2017, 91(1), 879-893.
Rodríguez, G. Quintana, A. Bustillo & J. Ciurana, A decision-making tool based on decision trees for roughness prediction in face milling, International Journal of Computer Integrated Manufacturing, 2017, 30(9), 943-957.
Palasciano, A. Bustillo, P. Fantini, M. Taisch, A new approach for machine´s management: from machine´s signal acquisition to energy indexes, Journal of Cleaner Production, 2016, 137, 1503-1515.
Bustillo, L.N. López de Lacalle, A. Fernández-Valdivielso, P. Santos, Data-mining modeling for the prediction of wear on forming-taps in the threading of steel components, Journal of Computational Design and Engineering, 2016, 3, 337-348.
Bustillo, M. Grzenda, B. Macukow, Interpreting tree-based prediction models and their data in machining processes, Integrated Computer-Aided Engineering, 2016, 23(4), 349-367, DOI: 10.3233/ICA-160513
Bustillo, M. Alaguero, I. Miguel, J. M. Saiz, L. S. Iglesias, A flexible platform for the creation of 3D semi-immersive environments to teach Cultural Heritage, Digital Applications in Archaeology and Cultural Heritage 2015, 2(4), 248-259, DOI:10.1016/j.daach.2015.11.002.
Arnaiz-Gonzalez, A. Fernandez-Valdivielso, A. Bustillo, L. N. Lopez de Lacalle, Using artificial neural networks for the prediction of dimensional error on inclined surfaces manufactured by ball-end milling, International Journal of Advanced Manufacturing Technology, 2016, 83(5), 847-859.
Santos, L. F. Villa, A. Reñones, A. Bustillo, J. Maudes, An SVM-based solution for fault detection in wind turbines, Sensors, 15, 2015, 5627-5648.
Bustillo, J. J. Rodriguez, Online breakage detection of multitooth tools using classifier ensembles for imbalanced data, International Journal of Systems Science, 2014, 45(12), 2590-2602.
Bustillo, I. Oleaga,, J. J. Zualika, N. Loix, New methodology for the design of ultra-light structural components for machine-tools, International Journal of Computer Integrated Manufacturing, 2015, 28(4), 339-352.
Teixidor, M. Grzenda, A. Bustillo, J. Ciurana, Modeling pulsed laser micromachining of micro geometries using machine-learning Techniques, Journal of Intelligent Manufacturing, 2015, 26(4), 801-814.
Gorrotxategui, E. Porras, A. Bustillo, Nuevas propuestas para el mecanizado ecológico de componentes de titanio aeronáutico, Técnica y Tecnología, Septiembre 2013, 32-38.
Grzenda, A. Bustillo, The Evolutionary Development of Roughness Prediction Models, Applied Soft Computing, 13(5), 2013, 2913-2922.
Quintana, A. Bustillo, J. Ciurana, Prediction, monitoring and control of surface roughness in high-torque milling machine operations, International Journal of Computer Integrated Manufacturing, 25(12), 2012, 1129-1138.
Gajate, A. Bustillo, R. E. Haber, Transductive neurofuzzy-based torque control of a milling process: results of a case study, International Journal of Innovative, Computing, Information and Control, 8(5), 2012, 3495-3510.
Grzenda, A. Bustillo, P. Zawistowski, A soft computing system using intelligent imputation strategies for roughness prediction in deep drilling, Journal of Intelligent Manufacturing, 23(5), 2012, 1733-1743.
Bustillo, M. Correa, Using artificial intelligence to predict surface roughness in deep drilling of Steel Components, Journal of Intelligent Manufacturing, 23(5), 2012, 1893-1902.
F. Díez-Pastor, A. Bustillo, G. Quintana and C. García-Osorio, Boosting Projections to improve surface roughness prediction in high-torque milling operations, Soft Computing, 16(8), 2012, 1427-1437.
Gajate, R. E. Haber, R. M. del Toro-Matamoros, P. Vega, A. Bustillo, Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process, Journal of Intelligent Manufacturing, 23(3), 2012, 869-882.
Grzenda, A. Bustillo, G. Quintana and J. Ciurana, Improvement of surface roughness models for face milling operations through dimensionality reduction, Integrated Computer-Aided Engineering, 19(2), 2012, 179-197.
Reñones, A. Bustillo, G. Quintana, S. Saludes, ¿Qué pueden hacer los sensores inteligentes en una planta de fabricación? Industria Metalmecánica 217 Época 2ª – Nº 911 / Abril 2012, 76-83.
Bustillo, J.F. Díez-Pastor, G. Quintana and C. García-Osorio, Avoiding neural network fine tuning by using ensemble learning: application to ball-end milling operations, The International Journal of Advanced Manufacturing Technology, 57(5), 2011, 521-532.
Bustillo, L. M. Plaza, M. Rodriguez, New Strategy for the Optimal Design and Manufacture of High Performance Milling Heads, Revista de Metalurgia, 47 (6), 2011, 462-476.
Bustillo, E. Ukar, J. J. Rodriguez, A. Lamikiz Modelling of process parameters in laser polishing of steel components using ensembles of regression trees, International Journal of Computer Integrated Manufacturing, 24(8), 2011, 735-747.
Bustillo, M. Correa, A. Reñones, A virtual sensor for online fault detection of multitooth-tools, Sensors, 11, 2011, 2773-2795.
Yagüe, R. Rodríguez, J. A. García, A. Bustillo, F. Garciandía, F. Zubiri, Estudio del efecto de tratamientos dúplex temple laser + PVD en aceros de herramientas, TRATER Press, 11, 31-35, Junio 2009.
Bustillo, N. López de Lacalle, Nada de tecnología ficción. La inteligencia en las máquinas, algo más que un atractivo enunciado, IMHE, Información de máquinas-Herramienta, equipos y accesorios, Nº 360, 103-119, Mayo 2009.
M. del Toro-Matamoros, R. E. Haber, J. Pamies, A. Bustillo, Modelado y simulación del proceso de fresado a alta velocidad en MATLAB-SIMULINK, Revista de Metalurgia, 44(2), 2008, 176-188.
Norberto López de Lacalle, Andres Bustillo, Mecanizado a alta velocidad. Una imagen del presente,IMHE, Información de máquinas-Herramienta, equipos y accesorios, Septiembre 2008, 29-42. nº 351.
Sekler , A. Dietmair, A. Dadalau , H. Rüdele , J. Zulaika, J. Smolik, A. Bustillo, “Energy Efficient Machine by Means of Mass Reduction”, W T Werkstattstechnik-Forschung und Entwicklung fur die Produktion, Vol 5 (2007), 320-327, Junio 2007.
Dietmair, P. Sekler, J. Larrañaga, J. Sveda, M. Sulitka, A. Bustillo, Vibration reduction for production machines, W T Werkstattstechnik-Forschung und Entwicklung fur die Produktion, Vol 5 (2007), 307-313, Junio 2007.
Ramirez, J.R Alique, A. Bustillo Dispositivo para la Evaluación y Diagnóstico del Estado del Cabezal en Centros de Mecanizado de Alta VelocidadInf. tecnol., 2006, vol.17, no.4, p.23-28. ISSN 0718-0764.