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Prediction, monitoring and control of surface roughness in high-torque milling machine operations.

, , and . Int. J. Comput. Integr. Manuf., 25 (12): 1129-1138 (2012)

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Considering User Experience Parameters in the Evaluation of VR Serious Games., , and . AVR (1), volume 12242 of Lecture Notes in Computer Science, page 186-193. Springer, (2020)Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth., , and . J. Intell. Manuf., 29 (5): 1045-1061 (2018)New methodology for the design of ultra-light structural components for machine tools., , , and . Int. J. Comput. Integr. Manuf., 28 (4): 339-352 (2015)Evaluation of the novelty effect in immersive Virtual Reality learning experiences., , , and . Virtual Real., 28 (1): 27 (March 2024)Virtual reality-based tool applied in the teaching and training of condition-based maintenance in induction motors., , , , and . IECON, page 1-6. IEEE, (2021)Towards higher machine-tool eco-efficiency with an Information Sharing Platform., , and . IECON, page 7548-7553. IEEE, (2013)Conventional Methods and AI models for Solving an Industrial an Industrial Problem., , , , and . EMS, page 317-322. IEEE Computer Society, (2008)Prediction, monitoring and control of surface roughness in high-torque milling machine operations., , and . Int. J. Comput. Integr. Manuf., 25 (12): 1129-1138 (2012)Improvement of surface roughness models for face milling operations through dimensionality reduction., , , and . Integr. Comput. Aided Eng., 19 (2): 179-197 (2012)Semi-supervised roughness prediction with partly unlabeled vibration data streams., and . J. Intell. Manuf., 30 (2): 933-945 (2019)