In this paper the objective of this work is to develop a model to simulate the vibrational
effects of rotating machine parts on the single point cutting tool and cutting force acting on single
point cutting tool in turning. In this paper experimental studies were performed on turning process &
vibration is measured with the help of accelerometer along with a device called as Fast Fourier
Transformer (FFT) Analyzer and cutting force is measured with the help of Tool dynamometer. The
vibration of single point cutting tool is sensed by accelerometer located on the tool-post of lathe
machine. The accelerometer will send the sensed vibration to FFT Analyzer which can be convert the
sensed data by using accelerometer shown in PC such as frequency, Amplitude, displacement & so
on and cutting force is sensed by strain gauges which are compacted in tool post. The sensed force
will send to dynamometer, it displays the cutting force. The obtained experimental data given to an
Artificial Neural Network (ANN) in Matlab, with the help of experimental data ANN is to be trained.
And by using ANN can predict the vibrations and cutting force by changing parameters of turning
such as spindle speed, feed & depth of cut. This model of ANN can be predict vibrations of single
point cutting tool and cutting force acting on single point cutting tool to avoid the failure of cutting
tool.
12. Fig. 7: Comparison of Experimental Predicted Vibrations of Train data Test data
respectively
Table no. 4: Error between Experimental values Predicted values
Sr.
No.
Vibration (RMS) Cutting Force (kN)
Experimental Predicted % Error Experimental Predicted % Error
1 1099 1073 2.41 38.3 40.1 4.5
2 614 614 0 13.4 13.56 1.2
3 981 981 9 27.9 26.85 3.93
4 1463 1463 3.76 39.6 37.21 6.41
5 700 700 2.94 10.3 10.16 1.38
6 851 851 0 19.2 19.5 1.5
7 1001 1001 0 25.6 26.12 2
8 819 810 1.11 11.7 10.3 13.6
9 1122 1105 1.54 24.4 23.7 2.95
6. CONCLUSION
From the results it can be easily seen that the minimum error obtained for the predicted value
of test data. This study concludes that the model of ANN can be predict the vibrations cutting
force of single point cutting tool at any three parameters such as spindle speed, feed depth of cut.
And this predicted value is nearly equal to actual value of vibrations cutting force respectively. So
with the help of ANN model we can easily predict the vibrations cutting force of single point
cutting tool without any experiment. And effectiveness of ANN model can be improved by
modifying the number of layers and nodes in the hidden layers of the ANN network structure.