Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/58097
Title: Development of a predictive model for stress distributions at the tool-chip interface in machining
Authors: Li, X. 
Keywords: Metal cutting
Prediction
Slip-line filed
Stress distribution
Theoretical modelling
Tool-chip interface
Issue Date: Jan-1997
Citation: Li, X. (1997-01). Development of a predictive model for stress distributions at the tool-chip interface in machining. Journal of Materials Processing Technology 63 (1-3) : 169-174. ScholarBank@NUS Repository.
Abstract: In metal cutting, in order to monitor the machining characteristic factors, such as cutting temperature and tool wear, it is necessary to predict the normal and shear stresses at the tool-chip interface. The development of a predictive model for the stress distributions is presented in this paper. The model is firstly considered to be developed based on the power law assumption of stress distributions suggested by Zorev [1]. Equations for the stress distributions are derived, in which the normal and shear stresses are expressed as functions of cutting conditions, tool geometry, cutting forces and tool-chip contact length. Experimentally measured results for the tool-chip contact length and a slipline field analysis correlating the normal stress distribution and chip secondary plastic deformation at the tool-chip interface are used to test the predicted stress distributions. It is found that the power law assumption can not be used for the predictions because there are large discrepancies between the predicted and experimental results. Therefore, a new assumption for the stress distributions is proposed and the corresponding predictive model is developed. Using the new model, stress distributions at the tool-chip interface can be predicted from cutting conditions, tool geometry, and cutting forces, with the tool-chip plastic and total contact lengths being predicted as part of the solution. Well agreement between the predicted and experimental results is presented.
Source Title: Journal of Materials Processing Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/58097
ISSN: 09240136
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

50
checked on Nov 10, 2018

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.