TY - JOUR
T1 - Review of empirical modelling techniques for modelling of turning process
AU - Garg, A.
AU - Bhalerao, Y.
AU - Tai, K.
PY - 2013
Y1 - 2013
N2 - The most widely and well known machining process used is turning. The turning process possesses higher complexity and uncertainty and therefore several empirical modelling techniques such as artificial neural networks, regression analysis, fuzzy logic and support vector machines have been used for predicting the performance of the process. This paper reviews the applications of empirical modelling techniques in modelling of turning process and unearths the vital issues related to it.
AB - The most widely and well known machining process used is turning. The turning process possesses higher complexity and uncertainty and therefore several empirical modelling techniques such as artificial neural networks, regression analysis, fuzzy logic and support vector machines have been used for predicting the performance of the process. This paper reviews the applications of empirical modelling techniques in modelling of turning process and unearths the vital issues related to it.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-84883578713&partnerID=MN8TOARS
U2 - 10.1504/IJMIC.2013.056184
DO - 10.1504/IJMIC.2013.056184
M3 - Article
VL - 20
JO - International Journal of Modelling, Identification and Control
JF - International Journal of Modelling, Identification and Control
SN - 1746-6172
IS - 2
ER -