The main goal of this paper is to study the feasibility of using multiresolution analysis through the use of wavelet transform, to analyze the tool vibration signal, in order to indirectly establishing the end of turning tool life. To do so, several turning experiments were carried out with different cutting conditions and the tool vibration was measured using accelerometers. After the cuttings, the vibration signals were analyzed in time domain, frequency domain and time-frequency domain and their behaviors were compared with the workpiece surface roughnesses. As the tool wears, the workpiece roughness increases and the tool vibration signal change its features. So, it was necessary to extract from the signal the feature that follows the surface roughness behavior in order to establish the end of tool life based on the workpiece roughness criterion. The analysis was done on the acceleration (signal generated by the sensor), velocity (first integration of the signal) and displacement (second integration) of the tool. The main conclusion of this work is that, the best parameter of the tool vibration signal to follow the surface roughness behavior, is the second level inverse of the wavelet transform of the tool displacement signal.193426437Akihito, N., Fujita, S., Development of a Cutting Tool Failure Detector (1989) Bulletin of the Japan Society of Precision Engineering, 32, pp. 134-139Bonifácio, M.E.R., Diniz, A.E., Correlating Tool Wear, Tool Life, Surface Roughness and Tool Vibration in Finish Turning with Coated Carbide Tools (1994) Wear, 173, pp. 137-144Bonifácio, M.E.R., Diniz, A.E., Monitoring the Tool Life in Finish Turning Using Vibration Signals (1994) Journal of the Brazilian Society of Mechanical Sciences, 16, pp. 56-71Cohen, A., (1986) Biomedical Signal Processing, , CRC Press, Florida, USADaubechies, I., (1992) Ten Lectures on Wavelets, , SIAM, Philadelphia, USAGrabec, I., Susic, E., Application of a Neural Network to the Estimation of Surface Roughness from AE Signals Generated by Friction Process (1995) International Journal of Machine Tools and Manufacture, 35 (8), pp. 1077-1086Graham, T.S., Monitoring the Unmanned Machining (1989) FMS Magazine, 3 (7), pp. 127-131Jiang, Y.C., Xu, J.H., In Process Monitoring of Tool Wear Stage by the Frequency Band Energy Method (1987) Annals of the CIRP, 36, pp. 45-48Kasashima, N., Mori, K., Ruiz, G.H., Diagnosing Cutting Tool Conditions in Milling Using Wavelet Transform (1994) Bulletin of the Japan Society for Precision EngineeringLie, S., Elbestawi, M.A., Du, R.X., Tool Condition Monitoring in Turning Using fuzzy Set Theory (1992) International Journal of Machine Tools and Manufacture, 32 (6), pp. 781-796Mc Laughlin, C., Tansel, I.N., Mekdeci, C., Detection of Tool Failure in End Milling with Wavelet Transformations and Neural Networks (1995) International Journal of Machine Tools and Manufacture, 35 (8), pp. 1137-1147Meyer, Y., (1993) Wavelets, Algorithms and Applications, , SIAM, Philadelphia, USANewland, D.E., (1993) An Introduction to Random Vibrations, Spectral and Wavelet Analysis, , Longman Scientific & Technical, EnglandNicolescu, M., Carlsson, T., Bejhem, M., The Use of Vibration Signal in cutting Process Monitoring (1995) Proceedings of the 1st International Machining and Grinding Conference, , Ann Arbor, MichiganRao, S.B., Tool Wear Monitoring Through the Dynamics of Stable Turning (1986) ASME Journal of Engineering for Industry, 108, pp. 184-196Rioul, O., Vetterli, M., Wavelets and Signal Processing (1991) IEEE Signal Processing Magazine, 91 (10), pp. 14-38Shaw, M.C., (1984) Metal Cutting Principles, , Clarendon Press, OxfordSokolowski, A., Kosmol, J., Utilization of Vibration Measurements of Machine Tool Elements in the Monitoring of the Cutting Tool Conditions (1991) Proceedings of the 4th World Meeting on Acoustic Emission and 1st International Conference on AE in Manufacturing, pp. 327-333Tadao, K., Hiroshi, O., Akinori, N., Eiji, K., Application of Wavelet Analysis to Monitoring of Cutting Conditions in Milling (1994) Bulletin of the Japan Society of Precision Engineering, pp. 345-350Williams, J., Amaratunga, K., Introduction to Wavelets in Engineering (1994) International Journal for Numerical Methods for Engineering, 37 (6), pp. 2365-2388