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|Title:||Development of a predictive model for stress distributions at the tool-chip interface in machining||Authors:||Li, X.||Keywords:||Metal cutting
|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 . 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|
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