TRIBOLOGICAL CHARACTERIZATION AND PREDICTIVE MODELLING OF TOOL WEAR IN DRY CNC MILLING OF BRITTLE CERAMIC CORES USING MACHINE LEARNING METHODS

Ravikanna, R., Darbar, Y., Urch, M. et al. (3 more authors) (Accepted: 2026) TRIBOLOGICAL CHARACTERIZATION AND PREDICTIVE MODELLING OF TOOL WEAR IN DRY CNC MILLING OF BRITTLE CERAMIC CORES USING MACHINE LEARNING METHODS. In: 51st Leeds-Lyon Symposium on Tribology. 51st Leeds-Lyon Symposium on Tribology, 02-04 Sep 2026, Lyon, France. . (In Press)

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Item Type: Conference abstract
Authors/Creators:
Dates:
  • Accepted: 30 April 2026
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds)
Funding Information:
Funder
Grant number
TSB (KTP) Technology Strategy Board, Knowledge Transfer
10150263
Date Deposited: 24 Jun 2026 14:16
Last Modified: 24 Jun 2026 14:16
Status: In Press
Open Archives Initiative ID (OAI ID):

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