Abstract
Study was carried out to analyze the dynamic cutting signals of slot-milling process, in order to design automated on-line tool and surface roughness monitoring strategies, based on indices extracted from these signals, to automatically monitor and control surface roughness in slot milling.
Especially designed and manufactured sensitive strain gage dynamometer was used to measure slot-milling radial and tangential forces during milling cycle. The dynamometer was calibrated in static and dynamic ranges.
The effect of flank wear width on the magnitude of the cutting force harmonics was constructed as function of axial depth of cut, feed rate per tooth, specific cutting pressure of work material and instantaneous angle of rotation. The results were plotted at various cutting conditions in time and frequency domains.
The tool wear was measured in an off-line manner using the tool maker’s microscope and interrelationships of cutting force harmonics and tool wear magnitude were constructed and were used in the computer simulation. Surface roughness was measured using surface meter (Surtronic 3+) with a portable printer.
The cutting force signal harmonics were used to establish the proposed force based model to predict the surface roughness of the workpiece machined in slot-milling and examining this system by another experimental tests to define the reliability of the system and to define the percentage error of the system model. Hence, an index named as surface index (S.I) is extracted from ratio between first force amplitude at first significant frequency and first surface amplitude at the same frequency, to predict the surface roughness of the workpiece machined in slot-milling. This is to be employed in automated on-line quality management (monitoring and control) strategy.
