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A new experimental approach to identify, the cutting dynamics in turning operations is presented. This method treats the problem as a closed-loop gray-box identification problem and is based upon spectral analysis and least squares estimation techniques. An active magnetic bearing is employed both to excite the system and to increase the tool's damping. The inherent time delay of the cutting process is 'removed' in identification by limiting the observation period to less than one revolution period of the workpiece. The coefficients of several cutting tests were identified. The methodology was validated by predicting the critical depth of cut from the identification results and comparing with the experiment result measured from a cutting test. [DOI: 10.1115/1.2034509]

Abstract: This study discussed the development of the first and second order power prediction model for milling 618 stainless steel with coated carbides cutting tool. The first and second order [...]

In intelligent machine tools, a computer based control system, which can adapt the machining parameters in an optimal fashion based on sensor measurements of the machining process, should be incorporated. In this paper, the method for adaptive optimization of the cutting conditions in a face milling operation for maximizing the material removal rate is proposed. The optimization procedure described uses an exterior penalty function method in conjunction with a multilayered neural network. Two neural networks are introduced: one for estimating tool wear length, and the other for mapping input and output relations from the experimental data during cutting. The adaptive optimization of the cutting conditions is then implemented using the tool wear information and predicted process output. The results are demonstrated with respect to each level of machining such as rough, fine, and finish cutting.

An enhanced model for the prediction of static cutting forces in face milling is presented. The key features of the model include the ability to handle complex workpiece geometry, two-dimensional cutter feed paths, multiple pass machining, and effects of machine set-up errors. A two-dimensional boundary representation scheme is used to describe the workpiece geometry which may contain holes, slots, and other complex geometrical features. Variable cutter feed paths are represented by a combination of linear and circular arcs. In view of this and the complex workpiece geometry, a new algorithm for cutter-workpiece engagement determination is developed. Several sources of machine set-up error such as spindle and cutter axis tilt, and cutter center offset runout are modeled and their individual as well as combined effects on key machining process variables such as the axial and the radial depth of cut illustrated. Results of model verification experiments are reported for different workpiece geometry and cutter feed paths. A comparison of the predicted and measured forces shows good agreement.

In-plane stress distribution in a spinning free-clamped slicing blade is studied analytically. The blade is subjected to a stationary, distributed, in-plane slicing load along the inner periphery, while it is clamped and tensioned initially in the radial direction along the outer boundary. The radial, hoop, and shear stresses in the blade are given by sum of the stresses from the tensioning, spinning, and edge loading. The solution is obtained by introducing the Lame potential functions and the two- dimensional elasticity theory. Numerical results are presented for an actual SUS301 blade cutting a 6-in.-diameter silicon ingot at 1550 rpm. Results obtained show that the contribution of the slicing load on the stress distribution is not significant; further the overall stress distribution is approximated by that of the initial tensioning except for the case of the shear stress distribution.