Development of a tool wear-monitoring system for hard turning

180 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Advancing Cutting Technology (2003, methodology): “A recent development has been mapped on tool condition monitoring for hard turning [152].”
Machining Parameters Optimization of Titanium Alloy using Response Surface Methodology and Particle Swarm Optimization under Minimum-Quantity Lubrication Environment (2016, background): “The results showed that dynamic NN models can follow any development of wear and they forefend the monitoring system against possible disturbances that may cause it to soothsay erroneous values [21].”
Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks (2005, methodology): “Scheffer et al. [28] developed an online tool wear monitoring system for hard turning by using a similar approach proposed by Ghasempoor et al. [22].”
A review of flank wear prediction methods for tool condition monitoring in a turning process (2012, methodology): “Scheffer et al. [102] used time – frequency analysis with spectrograms in order to identify the most stationary parts of force signals for frequency domain analysis.”