Publicaciones en las que colabora con Pedro Jose Arrazola Arriola (26)
2024
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Correcting distortions of thin-walled machined parts by machine hammer peening
Chinese Journal of Aeronautics, Vol. 37, Núm. 6, pp. 439-453
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Hole quality improvement in CFRP/Ti6Al4V stacks using optimised flow rates for LCO2 and MQL sustainable cooling/lubrication
Composite Structures, Vol. 329
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Tool Geometry Optimisation for LCO2 Assisted Milling of Ti6Al4V
Procedia CIRP
2023
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A mechanistic-finite element hybrid approach to modelling cutting forces when drilling GFRP-AISI 304 stacks
CIRP Annals, Vol. 72, Núm. 1, pp. 69-72
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Corrigendum to “Improving surface integrity when drilling CFRPs and Ti-6Al-4V using sustainable lubricated carbon dioxide” [Chin. J. Aeronaut. 36(7) (2023) 129–146, (S1000936122001960), (10.1016/j.cja.2022.09.004)]
Chinese Journal of Aeronautics
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Effect of Post-Processing Treatment on Fatigue Performance of Ti6Al4V Alloy Manufactured by Laser Powder Bed Fusion
Journal of Manufacturing and Materials Processing, Vol. 7, Núm. 4
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Improving surface integrity when drilling CFRPs and Ti-6Al-4V using sustainable lubricated liquid carbon dioxide
Chinese Journal of Aeronautics, Vol. 36, Núm. 7, pp. 129-146
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Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning
Procedia CIRP
2022
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Effect of Tool Geometry and LCO2 Cooling on Cutting Forces and Delamination when Drilling CFRP Composites Using PCD Tools
Procedia CIRP
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Enhancing surface integrity of A7050-T7451 aluminium alloy by pneumatic machine hammer peening
Procedia CIRP
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Physical modelling with experimental validation of high ductility metal cutting chip formation illustrated by copper machining
International Journal of Machine Tools and Manufacture, Vol. 173
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Prediction of Surface Roughness of SLM Built Parts after Finishing Processes Using an Artificial Neural Network
Journal of Manufacturing and Materials Processing, Vol. 6, Núm. 4, pp. 82
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Sensitivity Analysis of Various Geometries of PCD and Cemented Tungsten Carbide Cutting Tools during the Milling of GFRP Composite
Polymers, Vol. 14, Núm. 8
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Sensor signal selection for tool wear curve estimation and subsequent tool breakage prediction in a drilling operation
International Journal of Computer Integrated Manufacturing, Vol. 35, Núm. 2, pp. 203-227
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Surface roughness assessment on hole drilled through the identification and clustering of relevant external and internal signal statistical features
CIRP Journal of Manufacturing Science and Technology, Vol. 36, pp. 143-157
2021
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An analytical approach to calculate stress concentration factors of machined surfaces
International Journal of Mechanical Sciences, Vol. 190
2020
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Estimación cualitativa de la rugosidad mediante algoritmos de aprendizaje automático en una operación de taladrado
Revista DYNA, Vol. 95, Núm. 5, pp. 487-491
2019
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Drilling test data from new and worn bits
Mondragon Unibertsitatea. Goi Eskola Politeknikoa
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Methodology to establish a hybrid model for prediction of cutting forces and chip thickness in orthogonal cutting condition close to broaching
International Journal of Advanced Manufacturing Technology, Vol. 101, Núm. 5-8, pp. 1357-1374
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The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process
International Journal of Advanced Manufacturing Technology, Vol. 102, Núm. 5-8, pp. 2133-2146