Neural network based prediction of drill wear from theoretically analysed and experimentally measured values of thrust force and torque

By Patra Karali   Bhattacharyya Kingshook   Pal Surjya K.  

International Journal of Machining and Machinability of Materials, Vol. 5, Iss. 2-3, 2009-02 ,pp. : 207-231

Inderscience Publishers

Access to resources Recommend Favorite

Prediction and comparison of thrust force and torque in drilling of natural fibre hybrid composite using regression and artificial neural network modelling

By Athijayamani A.   Natarajan U.   Thiruchitrambalam M.  

International Journal of Machining and Machinability of Materials, Vol. 8, Iss. 1-2, 2010-08 ,pp. : 131-145

Inderscience Publishers

Access to resources Recommend Favorite

Prediction of drill-bit breakage from degradation signals using Mahalanobis-Taguchi system analysis

By Rai Bharatendra K.   Chinnam Ratna Babu   Singh Nanua  

International Journal of Industrial and Systems Engineering, Vol. 3, Iss. 2, 2008-01 ,pp. : 134-148

Inderscience Publishers

Access to resources Recommend Favorite

Thrust force and delamination of core-saw drill during drilling of carbon fiber reinforced plastics (CFRP)

By Tsao C.  

The International Journal of Advanced Manufacturing Technology, Vol. 37, Iss. 1-2, 2008-04 ,pp. : 23-28

Springer Publishing Company

Access to resources Recommend Favorite

Prediction of thrust force and torque when drilling composite materials

By Bhatnagar Naresh   Jalutharia Mukesh Kumar   Singh Inderdeep  

International Journal of Materials and Product Technology, Vol. 32, Iss. 2-3, 2008-06 ,pp. : 213-225

Inderscience Publishers

Access to resources Recommend Favorite