✍ Scribed by Håkan Wiklund
No coin nor oath required. For personal study only.
In this paper, two statistical approaches to on-line prediction of cutting tool life are presented and discussed. A Bayesian approach utilizes in-process information about the cutting tool state and constitutes a valuable basis for improved prediction. A second approach is based on the cutting forces and facilitates a prediction of the tool life with an uncertainty of 15% after 1.5-2.0 cutting minutes. Traditional tool condition monitoring can be improved by increased reliability of tool life predictions, increased utilization of the cutting tools together with reduced need for pre-process data and calibrating procedures.
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