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Monitoring cutting tools is a strong need in automated un-manned production systems. However tool breakage detection should be separated from tool wear monitoring. The works presented in this paper show that Acoustic Emission (AE) can be used for detecting tool breakage in most conditions and an industrial system is available. Tool wear monitoring is much more complex. As demonstrated by some results in turning and milling, there are a great number of influencing parameters. It appears that AE has also capabilities for tool wear monitoring but no industrial system is presently available. Expert system or intelligent system such as Neural Networks using multiparameter appear to be the best solution for the future.

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