Zerrendatu Artikuluak-Ingeniaritza honen arabera: egilea "f9cfd74881df9f65494b7ae6f0b14c53"
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The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process
Duo, Aitor; Basagoiti, Rosa; ARRAZOLA, PEDRO JOSE; Aperribay Zubia, Javier; CUESTA ZABALAJAUREGUI, MIKEL (Springer Verlag, 2019)Industrial processes are being developed under a new scenario based on the digitalisation of manufacturing processes.Through this, it is intended to improve the management of resources, decision-making, ... -
Estimación cualitativa de la rugosidad mediante algoritmos de aprendizaje automático en una operación de taladrado
Duo, Aitor; Dominguez Romero, Erika; Azpitarte-Aranzabal, Larraitz; Aperribay Zubia, Javier; CUESTA ZABALAJAUREGUI, MIKEL; Garay, Ainara; Basagoiti, Rosa; ARRAZOLA, PEDRO JOSE (Federación de Asociaciones de Ingenieros Industriales de España, 2020) -
Sensor signal selection for tool wear curve estimation and subsequent tool breakage prediction in a drilling operation
Duo, Aitor; Basagoiti, Rosa; ARRAZOLA, PEDRO JOSE; CUESTA ZABALAJAUREGUI, MIKEL (Taylor & Francis, 2021)Tool condition monitoring have an important role in machining processes to reduce defective component and ensure quality requirements. Stopping the process before the tool breaks or an excessive tool wear is reached can ... -
Surface roughness assessment on hole drilled through the identification and clustering of relevant external and internal signal statistical features
Duo, Aitor; Basagoiti, Rosa; ARRAZOLA, PEDRO JOSE; CUESTA ZABALAJAUREGUI, MIKEL; Illarramendi, Miren (Elsevier, 2022)Drilling is a continuous cutting process where two or more cutting edges remove the material, to obtain the desired feature. During the chip evacuation, it generally rubs against the generated surface. Thus, the roughness ...