Abstract
Cognitive modelling of tool wear progress based on neural network supervised training, derived from investigational tool wear measurements during industrial turning of Inconel 718 aircraft engine products, is employed to obtain a dependable trend of tool wear curves for optimal utilisation of tool life and step increase of productivity, while preserving the surface integrity of the machined parts.
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