TY - JOUR
T1 - An analytical model for predicting specific cutting energy in whirling milling process
AU - He, Yan
AU - Wang, Lexiang
AU - Wang, Yulin
AU - Li, Yufeng
AU - Wang, Shilong
AU - Wang, Yan
AU - Liu, Chao
AU - Hao, Chuanpeng
PY - 2019/8/28
Y1 - 2019/8/28
N2 - The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90% accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.
AB - The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90% accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.
KW - whirling milling process
KW - specific cutting energy
KW - energy model
KW - cutting parameters
KW - material removal rate
UR - http://www.scopus.com/inward/record.url?scp=85071607721&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2019.118181
DO - 10.1016/j.jclepro.2019.118181
M3 - Article
SN - 0959-6526
VL - 240
SP - 1
EP - 16
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 118181
ER -
