Modelling cutting instability in rough turning 34CrNiMo6 steel
by Juho Ratava; Mika Lohtander; Juha Varis
International Journal of Operational Research (IJOR), Vol. 25, No. 4, 2016

Abstract: To maximise rough turning efficiency, using robust constant parameters or constant measured parameter adaptive control is not enough, but true adaptive control is needed. In order to safely optimise volume removal rate, it is necessary to model the cutting instability appearing at high levels of feed rate. This allows the prediction of the phenomenon and thus use of maximal cutting values while maintaining safe and controlled operation at all times by applying adaptive control. In this paper, various models are studied based on cutting parameters, sensor data and a combination of both. The capabilities of the models to classify cutting samples captured from the machining process are then examined and a model suitable for cutting condition prediction is recommended.

Online publication date: Thu, 10-Mar-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 Operational Research (IJOR):
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 subs@inderscience.com