A Data Dependent Systems Approach to Dynamics of Surface Generation in Turning

Abstract

A new investigative approach to metal cutting dynamics is proposed based on wavelength decomposition of surface roughness by data dependent systems (DDS). This approach distinguishes from the commonly used Fourier transform analysis. It is shown to be capable of throwing light on both macroscopic and microscopic aspects of cutting mechanics. Workpiece surfaces from turning experiments, changing only speed and only feed, are used to illustrate that the macro-effects of cutting conditions and vibrations can be related to RMS components due to large wavelengths of a few tenths of mm magnitude. In particular, the so-called Spanzipfel effect is accounted for and its RMS is derived. It is also shown that wavelengths of a few micrometer magnitude, estimated from the workpiece surface roughness, seem to provide an independent estimate of chip surface lamellar widths in micro-morphology, well in agreement with earlier investigations.