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The main objective of this paper is to develop a signal processing strategy using vibratory signals in order to provide an efficient tool wear monitoring system able to increase machining performance. The method is based on the changes in the vibration signatures acquired during the turning operation over the tool life. Several signal processing techniques based on time and frequency domain analysis are proposed in order to extract a large number of indicators of the cutting tool state as variance, kurtosis, skewness, and coherence function. In this work, one of the innovative results is the tracking of tool wear by variance and coherence estimation. All of these indicators are correlated and validated by using white light interferometry measurements. This paper focuses on the technologies used in monitoring conventional cutting operations and presents important findings related to this field.