Improving the accuracy of machine-learning models with data from machine test repetitions

The modelling of machining processes by means of machine-learning algorithms is still based on principles that are especially adapted to mechanical approaches, in which very few inputs are varied with little repetition of experimental conditions. These principles might not be ideal to achieve accura...

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Bibliographic Details
Published in:	Journal of intelligent manufacturing Vol. 33; no. 1; pp. 203 - 221
Main Authors:	Bustillo, Andres, Reis, Roberto, Machado, Alisson R., Pimenov, Danil Yu
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.01.2022 Springer Nature B.V
Subjects:	Accuracy Advanced manufacturing technologies Algorithms Angles (geometry) Artificial neural networks Business and Management Control Cooling systems Flooding Life prediction Machine learning Machines Manufacturing Mechatronics Medium carbon steels Model accuracy Modelling Neural networks Principles Processes Production Radial basis function Regression analysis Repetition Robotics Tool life Tool wear Tuning Turning (machining) Turning Brandsma facing tests Tool geometry Artificial intelligence Ensembles Machine learning
ISSN:	0956-5515, 1572-8145
Online Access:	Get full text
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