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Title: | Surface Properties and Corrosion Behavior of Turn-Assisted Deep-Cold-Rolled AISI 4140 Steel |
Authors: | Prabhu P.R. Prabhu D. Sharma S. Kulkarni S.M. |
Issue Date: | 2020 |
Citation: | Journal of Materials Engineering and Performance Vol. 29 , 9 , p. 5871 - 5885 |
Abstract: | In this research, the effect of various turn-assisted deep-cold-rolling process parameters on the residual stress, microstructure, surface hardness, surface finish, and corrosion behavior of AISI 4140 steel has been investigated. The examination of the surface morphology of the turned and processed samples was performed by using a scanning electron microscope, energy-dispersive spectroscopy, and atomic force microscopy. Response surface methodology and desirability function approach were used for reducing the number of experiments and finding local optimized conditions for parameters under the study. The results from the residual stress measurements indicate that the rolling force has the highest effect by generating a deeper layer of residual compressive stress. The outcomes of surface hardness and surface finish emphasize that rolling force and number of tool passes are the most significant parameters affecting the responses. Surface studies confirmed the corrosion and its intensity onto the metal surface, and according to atomic force microscopy studies, the surface had become remarkably rough after exposure to the corrosive medium. Improvements in surface microhardness from 225 to 305.8 HV, the surface finish from 4.84 down to 0.261 μm, and corrosion rate from 6.672 down to 3.516 mpy are observed for a specific set of parameters by turn-assisted deep-cold-rolling process. The multiresponse optimization for surface finish and corrosion rate together shows that a ball diameter of 10 mm, a rolling force of 325.75 N, initial roughness of 4.84 µm, and number of tool passes of 3 give better values for the two responses under consideration with composite desirability of 0.9939. Based on the experimental work at the optimum parameter setting, the absolute average error between the experimental and predicted values for the corrosion rate is calculated as 3.2%. © 2020, The Author(s). |
URI: | https://doi.org/10.1007/s11665-020-05051-x http://idr.nitk.ac.in/jspui/handle/123456789/15883 |
Appears in Collections: | 1. Journal Articles |
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