Modelling of the cutting forces in turning process for a new tool
by Aydin Salimiasl; Ahmet Özdemir
International Journal of Mechatronics and Manufacturing Systems (IJMMS), Vol. 9, No. 2, 2016

Abstract: In this paper, a neural network model (ANN) was created to predict the cutting forces in turning process for a new tool. A dynamometer was used to measure the static and dynamic cutting forces during the machining process. AISI 4140 steel was used as the work piece material due to its common application in machining industry. Cutting force, thrust force and radial force were measured for three combinations of cutting speeds (V), feed rates (f) and cutting depths (d). The tool angles were kept constant throughout the experiments. Full factorial method was used to design the experiments. For establishing the prediction model, a back propagation network (BPN) was developed with two layers and five neurons. Experimental results were compared with the predicted results of the neural network model (NN). The R2 values for training and test data were obtained 0.9992 and 0.9985 respectively.

Online publication date: Wed, 27-Apr-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mechatronics and Manufacturing Systems (IJMMS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email