AI for tribology: Present and future
With remarkable learning capabilities and swift operational speeds, artificial intelligence (AI)
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …
can assist researchers in swiftly extracting valuable patterns, trends, and associations from …
Integrating physics-informed recurrent Gaussian process regression into instance transfer for predicting tool wear in milling process
B Qiang, K Shi, N Liu, J Ren, Y Shi - Journal of Manufacturing Systems, 2023 - Elsevier
Effective management of tool condition is of key importance to produce precision parts with
desirable structural shape and excellent surface integrity. Due to the variable cutting …
desirable structural shape and excellent surface integrity. Due to the variable cutting …
A Review of Physics-Based, Data-Driven, and Hybrid Models for Tool Wear Monitoring
H Zhang, S Jiang, D Gao, Y Sun, W Bai - Machines, 2024 - search.proquest.com
Tool wear is an inevitable phenomenon in the machining process. By monitoring the wear
state of a tool, the machining system can give early warning and make advance decisions …
state of a tool, the machining system can give early warning and make advance decisions …
Bayesian neural networks modeling for tool wear prediction in milling Al 6061 T6 under MQL conditions
The integration of artificial intelligence, machine learning, and deep learning algorithms into
machining processes has made them more intelligent, significantly reducing costs …
machining processes has made them more intelligent, significantly reducing costs …