Abstract:
Presented in this work is a novel tool-condition criterion dubbed as the current rise criterion (CRC). This criterion is based on the measured current values of the machine tool’s spindle and drive motors. The CRC comprises two components: (1) the current rise index (CRI) and (2) a sensitivity factor (SF) indicated as a subscript to the CRI. Current rise criterion is described mathematically as CRC = CRISF. The CRI that accounts for the damage (including wear) suffered by the tool is calculated as the square root of the sum of the squared percent increase in the root mean square (RMS) current values of the spindle and drive motors. To indicate the relative contribution of each of the machine tool motors to the CRI, the sensitivity factor (SF) reflects the ratio of the drive motor current percent rise to that of the spindle motor. The reference current used in calculating the percent rise of the motor current for both CRI and SF is measured at the first cut of the fresh tool. The versatility of the CRC was demonstrated here using two different machining processes: milling and drilling. Quantitative polar maps of the CRI and the associated sensitivity factor of cutting tools as well as qualitative descriptions of the various modes of tool condition afflicting the cutting tools are presented. CRC is demonstrated to be capable of monitoring the tool condition for a variety of cutting parameters of speeds and feeds. Another study demonstrated the versatility of CRC as a discriminator of the quality of chisel drills. It was found that the criterion successfully tracks the tool condition along a variety of process levels. CRC may be used to monitor tool condition and prognostics across practically all machining operations and process parameters, thus rendering the criterion “process independent.” CRC can also be used to monitor the change in power consumption of machine tools while cutting with worn tools.
Citation:
Ammouri, A. H., & Hamade, R. F. (2014). Current rise criterion: a process-independent method for tool-condition monitoring and prognostics. The International Journal of Advanced Manufacturing Technology, 72(1-4), 509-519.