Improved analytical model for residual stress prediction in orthogonal cutting

Zhaoxu QI, Bin LI, Liangshan XIONG

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PDF(843 KB)
Front. Mech. Eng. ›› 2014, Vol. 9 ›› Issue (3) : 249-256. DOI: 10.1007/s11465-014-0310-1
RESEARCH ARTICLE

Improved analytical model for residual stress prediction in orthogonal cutting

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Abstract

The analytical model of residual stress in orthogonal cutting proposed by Jiann is an important tool for residual stress prediction in orthogonal cutting. In application of the model, a problem of low precision of the surface residual stress prediction is found. By theoretical analysis, several shortages of Jiann’s model are picked out, including: inappropriate boundary conditions, unreasonable calculation method of thermal stress, ignorance of stress constraint and cyclic loading algorithm. These shortages may directly lead to the low precision of the surface residual stress prediction. To eliminate these shortages and make the prediction more accurate, an improved model is proposed. In this model, a new contact boundary condition between tool and workpiece is used to make it in accord with the real cutting process; an improved calculation method of thermal stress is adopted; a stress constraint is added according to the volume-constancy of plastic deformation; and the accumulative effect of the stresses during cyclic loading is considered. At last, an experiment for measuring residual stress in cutting AISI 1045 steel is conducted. Also, Jiann’s model and the improved model are simulated under the same conditions with cutting experiment. The comparisons show that the surface residual stresses predicted by the improved model is closer to the experimental results than the results predicted by Jiann’s model.

Keywords

residual stress / analytical model / orthogonal cutting / cutting force / cutting temperature

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Zhaoxu QI, Bin LI, Liangshan XIONG. Improved analytical model for residual stress prediction in orthogonal cutting. Front. Mech. Eng., 2014, 9(3): 249‒256 https://doi.org/10.1007/s11465-014-0310-1

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Acknowledgments

The authors acknowledge the Foundation for Innovative Research Group of the National Natural Science Foundation of China (No. 51121002) and the National Basic Research Program of China (No. 2011CB706803).

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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