Monitoring of microturning process using acoustic emission signals
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The great challenge of modern industry is to carry out an online prediction in the shop floor during the machining to define the exact tool breakage instant and simultaneously improve the quality of manufactured products. Acoustic emission sensors have been used to monitoring traditional and non-traditional machining processes. This work shows a study of the online monitoring in the microturning process using an acoustic emission sensor. A factorial design was performed to examine the effect of the feed rate, depth of cut, cooling system, and the type of tool on the response acoustic emission signal. Moreover, the acoustic emission signal was correlated with surface roughness and microhardness. The results showed that the acoustic emission signals are sensitive with the progressive increase in surface roughness and the microhardness.
KeywordsMicroturning Microhardness Acoustic emission Surface roughness
The authors would like to thank the CNPq—National Research Council by financial support Grant Number 303431/2016-4 and Sandvik Coromant Company for supplying the tools.
Compliance with ethical standards
Conflict of interest
The authors declare that there is no conflict of interest.
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