The investigation of surface roughness in machined materials/products has proven to be a difficult undertaking. The surface quality is determined not only by the parameters but also by the cutting conditions. Surprisingly, a study indicated that when analysing the quality of machining processes currently being done, surface morphology has a significant impact on tool performance. PCD (Polycrystalline diamond) and PCBN (Poly cubic boron nitride) cutting tools produce a better surface finish, which is explored in the machining of Al-Mg/Zr/TiO2 (15%), nano metal matrix composites (NMMC). The study primarily focuses on determining the best parameters for end milling NMMCs in tests for long-term production sustainability. Using scanning electron microscopy, microstructural study of the machined surface will aid in finding the parameters responsible for the cause of surface integrity. The work focusses on analysing tool performance by monitoring the machining process in real time using signal characteristics, forecasting vibrations (displacement) and machine outputs using surface topography and chip analysis. The tool failure was acquired by establishing a correlation between displacement (vibrations) and post machining outcome of experimental study, as a result, the evolution of displacement in the PCBN tool is 24.7 μm, which is better compared to 34.3 μm in the PCD tool at 3000 r/min. PCBN outperformed PCD with a 1.82 μm surface roughness, resulting in longer tool life. Thus, this economical reliable empirical method the problem of finding difficulty identifying the causing of tool wear and failure by correlating sensor signals features with experimental results.