This study establishes a tool condition monitoring methodology builds on the vibration signal attained via data acquisition system which is integrated with the in house developed adaptive controller for an end milling. As the quality of the products and the machine tool performance are the key parameters in maintaining machine stability. Proposed Adaptive control optimization system is validated with the experimentation trials and data analysis on 3 axis CNC milling machine. The rotational speed of the spindle and vibration signals is found to be reactive to milling cutter condition and therefore capable of sustaining the set-out methodology. A novel hybrid transformation, coupled with FFT and HHT is proposed to distinguish between a source of variation for adaptive control optimization, cutting region with the non-cutting region. In this study, decisions are made to evaluate the tool condition by combining all related information into a rule base. The investigation trajectories unveil the established system be able to accomplish the mechanism properly as anticipated.