Mikel Cuesta Zabaljauregui-rekin lankidetzan egindako argitalpenak (8)

2023

  1. A meta-learning strategy based on deep ensemble learning for tool condition monitoring of machining processes

    17th CIRP Conference on Intelligent Computation in Manufacturing Engineering

  2. Monitorización de estado de la herramienta en mecanizado mediante redes neuronales residuales robustas

    Congreso de Fabricación Avanzada y Máquinas-herramienta 2023 (23CMH). Donostia-San Sebastian, 25-27 de octubre, 2023

  3. Optimal Manufacturing Configuration Selection: Sequential Decision Making and Optimization using Reinforcement Learning

    Procedia CIRP

2022

  1. 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

  2. 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

2020

  1. 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

  1. Drilling test data from new and worn bits

    Mondragon Unibertsitatea. Goi Eskola Politeknikoa

  2. 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