The metal cutting operation has been affected very heavily by the ongoing development of the computing power of the microprocessors. This report addresses to one such application in "semiautonomous machining". The prime interest of this study is to obtain maximum metal removal rate while maintaining the surface finish of the workpieces at the desirable level. Characteristically these two targets introduce a trade-off and as a result an optimal operating condition. At an experimental sight a lathe is retrofitted with 3 actuators to control the spindle speed, the depth of cut and the feed rate of the turning process. A sensory device, dynamometer, is used to monitor the cutting forces in 3-D at the tip of the tool. These force readings are processed via a computer, in-situ, to update the operating conditions, i.e. cutting speed, chip thickness and feed rate. There is a complex statistical analysis to forecast the trend of the dynamic characteristics which inturn yields an "anticipatory control" action. Fundamental principles of DDS (Dynamic Data Systems) and Corresponding Time Series Analysis are used off-line to describe the nature of the dynamics. Once the discrete dynamics is obtained off-line, the real time optimal control becomes one of lesser complexity but is not treated in this text. Two different packages are used to compare the convergence in the statistical part of the study. A table of comparison is prepared. An analytical model is developed to configure the effects of various parameters in the cutting mechanism. The actual data registries of force vs. the analytical model comparison is made. The future development points are discussed in the direction of introducing autonomous machining capabilities to the tools.
"On the Forecasting of Lathe Cutting Dynamics(1)", Proc. SPIE 0557, Automatic Inspection and Measurement, (19 December 1985); doi: 10.1117/12.966273; https://doi.org/10.1117/12.966273