Virtual machine tool

Metrology of freeform shaped parts

Manufacturing of Dies and Molds

The thermal deformations of a CNC machine tool spindle are the major contributor of thermal error. It is very significant both theoretically and practically to study how to accurately simulate the thermal error of the spindle. Firstly, this paper proposes a method for computing the coefficient of convection heat transfer of the spindle surface by referencing the theory on computing the coefficient of convection heat transfer of a flat plate when air flows along it. Secondly, the temperature field and thermal errors of the spindle are dynamically simulated under the actions of thermal loads using the finite element method. Thirdly, the characteristics of heat flow and thermal deformation within the spindle are analyzed according to the simulation results. Fourthly, the selection principle of thermal key points, which are indispensable for building a robust thermal error model, is provided based on the thermal error sensitivity technology. At last, a verification experiment is implemented on a CNC turning center, and the results show the simulation results are satisfying to replace the experiment results for further studies.

Simulation of thermal behavior of a CNC machine tool spindle

This paper presents a machining potential field (MPF) method to generate tool paths for multi-axis sculptured surface machining. A machining potential field is constructed by considering both the part geometry and the cutter geometry to represent the machining-oriented information on the part surface for machining planning. The largest feasible machining strip width and the optimal cutting direction at a surface point can be found on the constructed machining potential field. The tool paths can be generated by following the optimal cutting direction. Compared to the traditional iso-parametric and iso-planar path generation methods, the generated MPF multi-axis tool paths can achieve better surface finish with shorter machining time. Feasible cutter sizes and cutter orientations can also be determined by using the MPF method. The developed techniques can be used to automate the multi-axis tool path generation and to improve the machining efficiency of sculptured surface machining.

A machining potential field approach to tool path generation for multi-axis sculptured surface machining

Optimization and dynamic adaptation of the cutter inclination during five-axis milling of sculptured surfaces

Abstract The accuracy of a milling machine is limited by thermal deformations. Although the deformations can be minimized by a good design, they cannot be completely avoided, and they depend on operating conditions. We show that a reduction and/or a compensation of these deformations is even more important when exploiting additional degrees of freedom, which is an additional motivation for our research efforts. A neural model was used to compensate thermal deformations of a five-axes milling machine. Neural nets were used because they can approximate complex multivariable non-linear relationships. First, a computer controlled test set-up was built to collect the training and test data. Then, a feedforward neural net was trained to estimate these deformations, given the temperature measurements. A backpropagation algorithm was used, modified with momentum and an adaptive learning rate. The maximum deformation of 150 μm was reduced to 15 u,m by using a single hidden layer with four neurons. Finally, the neural model was tested under operating conditions. Two workpieces were milled, one with and one without compensation. The neural model was able to reduce machining errors from 75 μm to 16μm With the presented approach, we managed to achieve successful results in a relatively short period, after first attempts had failed to reduce the deformations by eliminating the heat source.

Paul Klewais

Papers

Optimization and dynamic adaptation of the cutter inclination during five-axis milling of sculptured surfaces

Compensation of thermal deformations in machine tools with neural nets

Nc-Postprocessing And Nc-Simulation For Five-Axis Milling Operations With Automatic Collision Avoidance

An investigation of the surface characteristics in 5 axis milling with thoroid cutters