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Indian Journal of Engineering and Materials Sciences (IJEMS) >
IJEMS Vol.13 [2006] >
IJEMS Vol.13(4) [August 2006] >
| Title: | Prediction of tool wear in high speed machining using acoustic emission technique and neural network |
| Authors: | Giriraj, B
Raja, V Prabhu
Gandhinadhan, R
Ganeshkumar, R |
| Issue Date: | Aug-2006 |
| Publisher: | CSIR |
| IPC Code: | B23Q
G05B19/18 |
| Abstract: | High speed machining
(HSM) provides a lot of perks like higher productivity, better surface finish
and good accuracy but with the limitation of rapid tool wear rate. On-line tool
wear monitoring is therefore essential for a fully automated high speed
machining process. Acoustic emission (AE) technique has proven to be a better
tool wear monitoring method owing to its sensitivity, quick response time and
consistency. This work deals with the formulation of methodology and conduct
experiments for predicting the tool wear in high speed machining using acoustic
emission technique and artificial neural network (ANN). Taguchi’s design of
experiments has been used to optimize the number of experiment. The
experimental observations are used to train an artificial neural network to
predict the progressive tool wear. The outcome of the work includes the
selection of optimum cutting parameters for minimum tool wear, identification
of the percentage contribution of individual parameters towards tool wear and
the prediction of tool wear using artificial neural network with a maximum
deviation of 4%. |
| Page(s): | 275-280 |
| ISSN: | 0975-1017 (Online); 0971-4588 (Print) |
| Source: | IJEMS Vol.13(4) [August 2006]
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