Y.S. Tarng

Surface roughness inspection by computer vision in turning operations

The use of computer vision techniques to inspect surface roughness of a workpiece under a variation of turning operations has been reported in this paper. The surface image of the workpiece is first acquired using a digital camera and then the feature of the surface image is extracted. A polynomial network using a self-organizing adaptive modeling method is applied to constructing the relationships between the feature of the surface image and the actual surface roughness under a variation of turning operations. As a result, the surface roughness of the turned part can be predicted with reasonable accuracy if the image of the turned surface and turning conditions are given.

Modeling of the process damping force in chatter vibration

Abstract This paper presents a new mechanistic model to study the complex and highly nonlinear process damping force in chatter vibration. In the developed model, a feedforward neural network is used to model cutting force components. The process damping force due to the interface between the tool flank and machined surface is estimated through the calculation of the volume of the work material displaced by the tool flank. To properly calculate the volume of the displaced work material, the vibration of the tool relative to the workpiece is solved using the equations of motion iteratively until a convergence criterion is satisfied. The study has shown that the developed model is much better than previous models in the analysis of dynamic behaviors of the nonlinear process damping force in chatter vibration.

An analytical model of chatter vibration in metal cutting

Abstract A new analytical model of chatter vibration in metal cutting is presented. The basic cutting mechanics adopted in the model is derived from a predictive machining theory based on a shear zone model of chip formation. A feature of this model is that variations of the undeformed chip thickness and rake angle due to the machine tool vibration are taken into account in determining the cutting forces and the forces are then coupled with the equations of motion to solve for the vibrational amplitudes with iterative techniques. Non-linearities in dynamic cutting processes caused by the effects of tool disengagement from the cut and cutting process damping are also included in the model. It is shown that the proposed model can be applied to make predictions for the suppression of chatter vibration by a change of tool geometries.

A critical investigation of the phase shift between the inner and outer modulation for the control of machine tool chatter

The change of spindle speed has been recognized as an effective way to control machine tool chatter. This is because the change of spindle speed can adjust the phase shift between the inner and outer modulation. Chatter can then be suppressed or enlarged by using different phase shifts. However, it still needs to be clarified as to how the change in spindle speed is correlated with the phase shift for suppressing chatter. In this paper, the relationship between the spindle speed and phase shift is clearly studied. As a result, the behavior of chatter due to the adjustment of the phase shift between the inner and outer modulation can be understood in detail. Experimental results performed in drilling and milling operations are presented to illustrate the chatter control using the change of spindle speed.

Genetic synthesis of fuzzy logic controllers in turning

Abstract The paper presents an optimal fuzzy logic controller design using efficient robust optimization techniques called genetic algorithms. It is shown that genetic algorithms can automatically search input and output scaling factors, membership functions, and fuzzy rules of the fuzzy logic controllers based on a fitness function. As a result, fuzzy logic controllers with optimal control performance can be systematically constructed instead of using a time-consuming trial and error approach. An adaptive force control system in turning operations is then used to illustrate the proposed method. It is shown that the developed fuzzy logic controller can achieve an automatic adjustment of feed rate to optimize the production rate with a constant cutting force in turning operations.

A study of backlash on the motion accuracy of CNC lathes

In this paper, an analytical solution is reported to explain the experimentally observed backlash behaviors on the motion accuracy of CNC lathes. It is found that backlash occurs when the feed direction is reversed. Due to the imperfect transient response of the driving mechanism, not only the static backlash error but also the dynamic backlash error is generated on the contouring profile. A simple control strategy is then developed to reduce the static and dynamic backlash errors. Computational simulations and experimental results are presented to illustrate the proposed method.

Cross-coupled fuzzy logic control for multiaxis machine tools

Abstract This paper presents a design and implementation case study that focuses on contour control of a biaxial CNC machine tools. Since, it is difficult to obtain an accurate nonlinear mathematical model of cross-coupled multiaxis machine tools, here we investigate an alternative to conventional approaches where we employ crosscoupled fuzzy logic controllers for improving the contouring accuracy of multiaxis CNC machine tools. A new fuzzy rule-generated method which is based on a performance index of the contour error obtained from an on-line estimation algorithm is proposed. An adapted output scale factor is adopted to improve the system performance. Experimental results have shown that the desired contouring accuracy can be achieved, and the proposed approach outperforms over uncoupled approaches. In conventional control, increasing contour feedrate for productivity may result in larger contour errors. However, the experimental results have shown that the performance of the proposed approach is still quite good with increasing contour feedrate.

A self-organizing neural fuzzy logic controller for turning operations

This paper proposes a neural fuzzy logic controller to achieve self-organizing control for turning operations. A new learning method which is based on a performance index of sliding mode control is used for control rule modifications and some supervision rules are also given to secure rule modifications. One of the major advantages of the proposed model is that it can start from an empty control rule base. Simulation and experimental results of the control of a constant turning force under varying cutting conditions are given to illustrate the effectiveness of the proposed method.

An abductive network for predicting tool life in drilling

This paper presents an abductive network for predicting tool life in drilling operations. The abductive network is composed of a number of functional nodes. These functional nodes are well organized to form an optimal network architecture by using a predicted squared error criterion. Once the drill diameter, cutting speed and feedrate are given, tool life can be predicted based on the developed network. Experimental results have shown that the abductive network can be effectively used to predict drill life under varying cutting conditions and the prediction error of drill life is less than 10%.

Monitoring of drill fracture from the current measurement of a three-phase induction motor

The use of three-phase induction motor current to detect tool fracture in drilling operations is presented in this paper. The basic principles of three-phase induction motors are briefly described and then an equivalent circuit diagram of induction motors is given. Based on the equivalent circuit diagram, the square stator current of induction motors is approximately proportional to the electromagnetic torque developed by the motor. Since the occurrence of tool fracture will cause the variations in the motor torque, measurement of the stator current appears to be an indirect technique for sensing tool fracture. Experimental results have shown that drill fracture can be clearly recognized from the stator current of a three-phase induction spindle motor system.