Hardness Prediction of Grind-Hardening Layer Based on Integrated Approach of Finite Element and Cellular Automata

As an emerging composite processing technology, the grind-hardening process implements efficient removal on workpiece materials and surface strengthening by the effective utilization of grinding heat. The strengthening effect of grind-hardening on a workpiece surface is principally achieved by a hardened layer, which is chiefly composed of martensite. As a primary parameter to evaluate the strengthening effect, the hardness of the hardened layer mostly depends on the surface microstructure of the workpiece. On this basis, this paper integrated the finite element (FE) and cellular automata (CA) approach to explore the distribution and variation of the grinding temperature of the workpiece surface in a grind-hardening process. Moreover, the simulation of the transformation process of “initial microstructure–austenite–martensite” for the workpiece helps determine the martensite fraction and then predict the hardness of the hardened layer with different grinding parameters. Finally, the effectiveness of the hardness prediction is confirmed by the grind-hardening experiment. Both the theoretical analysis and experiment results show that the variation in the grinding temperature will cause the formation to a certain depth of a hardened layer on the workpiece surface in the grind-hardening process. Actually, the martensite fraction determines the hardness of the hardened layer. As the grinding depth and feeding speed increase, the martensite fraction grows, which results in an increase in its hardness value.

Modeling of the Evolution of the Microstructure and the Hardness Penetration Depth for a Hypoeutectoid Steel Processed by Grind-Hardening

Grind-hardening processing is an emerging approach that combines the grinding and surface quenching process. During the process, the hardened layer—mainly martensite—is produced on the surface of the workpiece to achieve the purpose of surface strengthening. Above all, the surface temperature field of the hypoeutectoid-1045 steel workpiece was determined by finite element method for fully revealing the formation mechanism of the hardened layer. Further, the cellular automata approach was applied to dynamically simulate the transformation of both austenitization and martensitization from the initial microstructure. The hardness penetration depth was also predicted. Finally, a grind-hardening experiment was conducted to assess the theoretical study. Results showed that a combination of the finite element method and the cellular automata approach can effectively simulate the microstructure transformation of hardened layer. The microstructure and the hardness penetration depth were affected by the maximum grinding temperature and the heating rate. Research on the influence of grinding parameters showed that the hardness penetration depth increased as the depth of the wheel cut and feeding speed increased. Experiments revealed that the difference between predicted value and experimental value of the hardness penetration depth varied between 2.83% and 7.31%, which confirmed the effectiveness of the predicted model.

Experiments and Regression Analysis of Grinding Hardened Layer Depth Based on Transverse Feed

Based on orthogonal experiments, the influences of grinding process parameters including depth of cut (ap), workpiece infeed velocity (vw) and transverse regrinding value (Cr) on hardened layer depth (HLD) of 40Cr steel are studied in the grind-hardening process. The grind-hardening orthogonal experiments of 3-factors are performed on the 40Cr steel with the L16 (45) orthogonal table and the experimental optimization design theory. To understand quantitatively the effects of three grinding process parameters, the experimental data are modeled by regression. Among three grinding process parameters, the most important parameter is ap, followed by vw and Cr respectively. The experimental results indicate that HLD would increase with the increasing of the depth of cut and the decreasing of the workpiece infeed velocity in grind-hardening process, but HLD would decrease with the increasing of the interaction between the depth of cut and workpiece infeed velocity.

Online Detection and Study of Cracks in Grinding Hardening

Grind-Hardening technology is a new technology for cutting that combines grinding theory with quenching theory, and the heat produced during the grinding process has a great effect on the surface quality of the parts. This paper take advantage of method of acoustic emission testing to test the grinding hardened parts by online or scene. The wavelet packet is used to denoise the signal, then the denoising signal is analyzed to judge those grinding cracks or defects that may appear on the surface of the parts, and besides, this method is easy to do.