Argitalpenak (23) Mikel Saez de Buruaga Echeandia argitalpenak

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2024

  1. Multivariate Adaptive Downsampling Algorithm for Industry 4.0 Visual Analytics

    Cybernetics and Systems, Vol. 55, Núm. 6, pp. 1399-1416

  2. SortAlign: a score-based aggregation technique for neural networks in one-round federated learning

    Systems Science and Control Engineering, Vol. 12, Núm. 1

2023

  1. Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

    Mechanical Systems and Signal Processing, Vol. 185

  2. Tool remaining useful life prediction using bidirectional recurrent neural networks (BRNN)

    International Journal of Advanced Manufacturing Technology, Vol. 125, Núm. 9-10, pp. 4027-4045

2022

  1. Mechanical properties of friction induced nanocrystalline pearlitic steel

    Scientific Reports, Vol. 12, Núm. 1

  2. 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

2021

  1. A novel machine learning‐based methodology for tool wear prediction using acoustic emission signals

    Sensors, Vol. 21, Núm. 17

  2. Experimental Investigation of Contact Forces and Temperatures in Rubbing Interactions of Honeycomb Interstate Seals

    Manufacturing Engineering Society International Conference, MESIC 9: Gijόn, 2021, Spain, June 23-24-25

2019

  1. Determination of emissivity and temperature of tool rake face when cutting AISI 4140

    Procedia Manufacturing

  2. Evaluation of different flow stress laws coupled with a physical based ductile failure criterion for the modelling of the chip formation process of Ti-6Al-4V under broaching conditions

    Procedia CIRP

  3. FEM modeling of hard turning 42CrMoS4 steel

    Procedia CIRP

  4. Innovative Method dedicated to the development of a ferrite-pearlite grade regarding its MAChinability (IMMAC)

    Innovative Method dedicated to the development of a ferrite-pearlite grade regarding its MAChinability: final report

  5. 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

  6. Microstructure based flow stress model to predict machinability in ferrite–pearlite steels

    CIRP Annals, Vol. 68, Núm. 1, pp. 49-52

  7. Modelización por elementos finitos del torneado de aceros en estado templado

    Revista DYNA, Vol. 94, Núm. 3, pp. 331-337

2018

  1. Determining tool/chip temperatures from thermography measurements in metal cutting

    Applied Thermal Engineering, Vol. 145, pp. 305-314

  2. Microstructural aspects of the transition between two regimes in orthogonal cutting of AISI 1045 steel

    Journal of Materials Processing Technology, Vol. 260, pp. 87-96

  3. New calibration method to measure rake face temperature of the tool during dry orthogonal cutting using thermography

    Applied Thermal Engineering, Vol. 137, pp. 74-82

2017

  1. A Coupled Eulerian Lagrangian Model to Predict Fundamental Process Variables and Wear Rate on Ferrite-pearlite Steels

    Procedia CIRP

2016

  1. Alfombra y escanér de seguridad

    Mold Press: Revista de moldes y matrices, Núm. 51, pp. 34-35