Tool condition monitoring (TCM) system in the industry are mainly used to detect tool wear, breakage and chatter on the tool. Tool wear of AISI P20 under various cutting conditions have been investigated in end milling using cutting force signals due flank wear progression. This study is focused on the piezoelectric sensor system which is integrated on rotating cutting tool for tool wear monitoring system in milling process. The signal captured by piezoelectric sensors are analyzed in time and frequency domain. The signal amplitudes of main cutting force, Fc in time domain are increased, while the peak of the amplitude in frequency domain is decreased as the flank wear and cutting speed increases. By using 3D I-kazTM statistical analysis method, the relationship and correlation between I-kaz coefficients, Z∞ values with resultant flank wear width data, VB are proved. The results show that 3D I-kazTM statistical analysis method can be effectively used to monitor tool wear progression using a wireless telemetry system during milling operations.