Abstract
In machining operation, there is frequent tool wearing and breakage. Many a times, the root cause for early failure of tool is inappropriate cutting forces. In milling operation, cutting force is an intrinsic phenomenon which plays important role in machine tool conditioning. Prediction of the cutting force by traditional modelling methods becomes time consuming and costly. Artificial Neural Network (ANN) gives an easier way of predicting force model in case of machining operations and it is best technique to be used when the process is non-linear and as the milling operation is non-linear and time dependent. This technique gives good result in lesser time. In this paper three feed forward backpropagation algorithms are compared on the basis of six different criterion to decide the best suited algorithm for predicting the cutting force in face milling.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
