1. Chien, W.-T. and
Tsai, C.-S.
, “The Investigation on the Prediction of Tool Wear and the Determination of Optimum Cutting Conditions in Machining 17-4PH Stainless Steel,” Journal of Materials Processing Technology 140, no. 1-3 (2003): 340-345, https://doi.org/10.1016/S0924-0136(03)00753-2.
2. Pal, S.K. and
Chakraborty, D.
, “Surface Roughness Prediction in Turning Using Artificial Neural Network,” Neural Computing & Applications 14, no. 4 (2005): 319-324, https://doi.org/10.1007/s00521-005-0468-x.
3. Kumanan, S.,
Nanne Saheb, S.K., and
Jesuthanam, P.
, “Prediction of Machining Forces Using Neural Networks Trained by a Genetic Algorithm,” Journal of the Institution of Engineers(India) Part PR, Production Engineering Division 87, no. 3 (2006): 11-15.
4. Magdum, V.B. and
Naik, V.R.
, “Tool Wear Monitoring When Turning EN 8 Steel with HSS-M2 Tool,” International Journal of Innovative Research in Science, Engineering and Technology 2, no. 5 (2013): 1706-1711.
5. Pradeesh, A.R.,
Mubeer, M.P.,
Nandakishore, B.,
Muhammed Ansar, K.
et al.
, “Effect of Rake Angles on Cutting Forces for a Single Point Cutting Tool,” Int Res J Eng Technol (IRJET) 3, no. 5 (2016).