Monday  |  Cedar  |  04:30 PM–04:50 PM

#17369, Control of Machining-induced Residual Stress via Tool Geometry and Process Parameter Modification

Distortion generated in machined, monolithic, thin-walled aerospace components due to residual stresses leads to significant material and economic waste in the manufacturing industry. Inherent residual stress (IRS) present in stock materials combines with machining-induced residual stress (MIRS) to influence the final machined part distortion. It is hypothesized that MIRS can be controlled, based on the part geometry, through deliberate cutting tool geometry and process parameter modifications to negate the effect of IRS on distortion, consequently resulting in distortion-free parts. A finite element (FE) orthogonal cutting model is developed to study how tool geometry and process parameters influence machining-induced residual stress (MIRS). Orthogonal cutting experiments are performed on Al 7075-T651 samples to measure cutting forces and MIRS. A cutting force dynamometer is used to measure forces during cutting and a novel digital image correlation (DIC) based hole drilling technique is employed to measure the near-surface residual stress (RS) in the cut samples. These data are subsequently utilized to validate the FE prediction model. Various cases of cutting simulations involving different depths of cut, tool tip radii, and rake angles are performed to study their effects on RS. Similar to prior literature, increasing the depth of cut, tool tip radius, or rake angle is found to promote the formation of near-surface tensile stresses. The competing effects of material ploughing and temperature are shown to determine the type of RS at the end of the cut. Moreover, a window of variation of RS (up to ±400 MPa) is estimated within the given range of conditions, allowing for the control of MIRS through tool and process modification.

Ritin Mathews   Oak Ridge National Lab
Avery Hartley   University of Kentucky
Charles Rohrer   University of Kentucky
Md Mehedi Hasan   University of Kentucky
Julius Schoop   University of Kentucky
Jaydeep Karandikar   Oak Ridge National Lab
Chris Tyler   Oak Ridge National Lab
Scott Smith   Oak Ridge National Lab