Bilatu
6-tik 1-6 emaitza erakusten
Estimación cualitativa de la rugosidad mediante algoritmos de aprendizaje automático en una operación de taladradoQualitative estimation of the roughness using automatic learning algorithms in a drilling operation
(Federación de Asociaciones de Ingenieros Industriales de España, 2020)
The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process
(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, ...
Sensor signal selection for tool wear curve estimation and subsequent tool breakage prediction in a drilling operation
(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
(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 ...
Drilling test data from new and worn bits
(2019)
This directory contains the raw data acquired by Mondragon Unibertsitatea during the execution of drilling tests. These data were used to obtain the results presented in the article "The capacity of statistical features ...