الفهرس 
Acknowledgement
Condition MonitoringOnly 14 pages are availabe for public view
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Abstract
Recently, cutting tool and product quality management in intelligent manufacturing has been implemented by automated tool and quality monitoring and control systems. These systems utilize born features recognized in indirect signals which reflect, on-line, the tool and quality conditions.
Study was carried out to analyze the synamic cutting signals of the drilling process, in order to design automated on-line tool and quality management strategies, based on indices extracted from these signals, to monitor and control drill modes of failures and hole quality, namely, drill whirling, flank wear and drill clogging, and the produced hole roundness error and profile shape.
Especially designed and manufactured strain gage dynamometer was used to measure the drilling thrust and torque during drikking cycle. The dynamometer was connected to strain gauge amplifiers with a hardware supported FFT analyzer controlled through personal computer. The workpiece vibration (accleration) in a direction perpendicular to the drill axis was measured using piezotron acclerometer connected to the FFT analyzer through piezotron coupler.
The pattern recognition technique; recently used in the on-line tool ans quality monitoring and control, was used.
A proposed mechanism for the whirling vibrations; which produce holes with high roundness errors and distorted polygon profiles, is presented, and the most sensitive signal to these errors was examined.
Hence, an index named as: Torque Amplitude Ratio (TAR) is extracted from torque signals, to predict and identify the roundness error and the profile shape of the hole under processing. This is to be employed in automated in-line quality management (monitoring and control) strategy and also to monitor the drill whirling.