Development of an online machining process monitoring system: Application in hard turning

A PXI-based online machining process monitoring system has been developed in LabVIEW environment. The developed monitoring system is capable to acquire, present and analyse sensory signals automatically by using advanced queue and triggering technique. The wavelet transform is explored to decompose sensory signals into static and dynamic components and extract features of tool malfunctions in machining processes. Statistical process monitoring technique is further proposed to construct thresholds of free-malfunction machining zone. Experimental results show that the developed online process monitoring system is effective to detect tool malfunctions and construct thresholds for free-malfunction machining zone. Finally, a critical analysis in terms of sensitivity and repeatability of alternative sensors versus a dedicated platform dynamometer has been carried out. The possibility to employ alternative sensing techniques in industrial environment has been investigated by turning experimental trials.