Experimental and numerical studies of AISI 1020 steel in grind-hardening

Currently, most of the researches studying grind-hardening have used Design of Experiments approach to obtain empirical correlations without any in-depth theoretical analyzes. In this paper, a comprehensive numerical model is developed to simulate the temporal and spatial temperature distributions of the workpiece under the dry grind-hardening condition using finite element method. The simulated hardness penetration depth is deduced from the local temperature distribution and time history of workpiece and its martensitic phase transformation conditions. The results from simulations are validated with experiments. The effect of two major grinding parameters, workpiece speed and depth of cut, on the hardness penetration depth are discussed

Prediction of 3D grinding temperature field based on meshless method considering infinite element

© 2018, Springer-Verlag London Ltd., part of Springer Nature. A three-dimensional numerical model to calculate the grinding temperature field distribution is presented. The finite block method, which is developed from meshless method, is used to deal with the stationary and the transient heat conduction problems in this paper. The influences of workpiece feed velocity, cooling coefficient, and the depth of cut on temperature distribution are considered. The model with temperature-dependent thermal conductivity and specific heat is presented. The Lagrange partial differential matrix from the heat transfer governing equation is obtained by using Lagrange series and mapping technique. The grinding wheel-workpiece contact area is assumed as a moving distributed square heat source. The Laplace transformation method and Durbin’s inverse technique are employed in the transient heat conduction analysis. The results of the developed model are compared with others’ finite element method solutions and analytical solutions where a good agreement is demonstrated. And the finite block method was proved a better convergence and accuracy than finite element method by comparing the ABAQUS results. In addition, the three-dimensional infinite element is introduced to perform the thermal analysis, and there is a great of advantages in the simulation of large boundary problems.The work was funded by China Scholarship Council, the Fundamental Research Funds for the Central Universities (N160306006), National Natural Science Foundation of China (51275084), and Science and technology project of Shenyang (18006001)

Characterization of innovative rotary swaged Cu-Al clad composite wire conductors

Cu/Al composites are perspective for applications in a wide range of industrial and commercial branches, from transportation to elecatrotechnics. This study focuses on Cu/Al clad composite wires with 5 mm diameter featuring unique sequencing produced via the technology of rotary swaging at the processing temperatures of 20 degrees C and 250 degrees C. During the swaging process, we continuously acquired samples for investigations and used our own KOMAFU S600 system for dynamic detection of swaging forces. The composite wires subjected to electrical resistivity measurement were further analysed via electron microscopy, neutron diffraction, and mechanical testing. The results showed that both the total imposed strain (swaging degree) and swaging temperature influenced the investigated parameters non-negligibly. The samples subjected to high reduction ratios (swaging degree > 3) at the temperature of 250 degrees C exhibited formation of intermetallics at the interfaces, which deteriorated the electric conductivity. However, the conductivity was also affected by structural phenomena, such as work hardening, texture development, dislocations density, and recrystallization. All the final 5 mm samples exhibited sufficient bonding of both the components and recrystallized ultra-fine grained structures providing them with the ultimate tensile strength of >200 MPa.Web of Science16083582

Numerical and Experimental Study on the Grinding Performance of Ti-Based Super-Alloy

The experiments of the surface grinding of Ti-6Al-4V grade 5 alloy (Ti-64) with a resin-bonded cubic Boron Nitride (cBN) grinding wheel are performed in this research to estimate the influence of cutting parameters named workpiece infeed speed, Depth of Cut (DOC), cooling condition on the grinding force, force ratio, and specific energy. A finite element simulation model of single-grain grinding of Ti-64 is also implemented in order to predict the values of grinding forces and temperature. The experimental results show that an increase of workpiece infeed speed creates higher intensified cutting forces than the DOC. The grinding experiments under wet conditions present slightly lower tangential forces, force ratio, and specific energy than those in dry grinding. The simulation outcomes exhibit that the relative deviation of simulated and experimental forces is in the range of 1-15%. The increase in feed rate considerably reduces grinding temperature, while enhancement of DOC elevates the heat generation in the cutting zone

Dry grinding technology for automotive gears manufacturing: process modeling and optimization

The following thesis focused on the dry grinding process modelling and optimization for automotive gears production. A FEM model was implemented with the aim at predicting process temperatures and preventing grinding thermal defects on the material surface. In particular, the model was conceived to facilitate the choice of the grinding parameters during the design and the execution of the dry-hard finishing process developed and patented by the company Samputensili Machine Tools (EMAG Group) on automotive gears. The proposed model allows to analyse the influence of the technological parameters, comprising the grinding wheel specifications. Automotive gears finished by dry-hard finishing process are supposed to reach the same quality target of the gears finished through the conventional wet grinding process with the advantage of reducing production costs and environmental pollution. But, the grinding process allows very high values of specific pressure and heat absorbed by the material, therefore, removing the lubricant increases the risk of thermal defects occurrence. An incorrect design of the process parameters set could cause grinding burns, which affect the mechanical performance of the ground component inevitably. Therefore, a modelling phase of the process could allow to enhance the mechanical characteristics of the components and avoid waste during production. A hierarchical FEM model was implemented to predict dry grinding temperatures and was represented by the interconnection of a microscopic and a macroscopic approach. A microscopic single grain grinding model was linked to a macroscopic thermal model to predict the dry grinding process temperatures and so to forecast the thermal cycle effect caused by the process parameters and the grinding wheel specification choice. Good agreement between the model and the experiments was achieved making the dry-hard finishing an efficient and reliable technology to implement in the gears automotive industry

Modeling and simulation of grinding processes based on a virtual wheel model and microscopic interaction analysis

Grinding is a complex material removal process with a large number of parameters influencing each other. In the process, the grinding wheel surface contacts the workpiece at high speed and under high pressure. The complexity of the process lies in the multiple microscopic interaction modes in the wheel-workpiece contact zone, including cutting, plowing, sliding, chip/workpiece friction, chip/bond friction, and bond/workpiece friction. Any subtle changes of the microscopic modes could result in a dramatic variation in the process. To capture the minute microscopic changes in the process and acquire better understanding of the mechanism, a physics-based model is necessary to quantify the microscopic interactions, through which the process output can be correlated with the input parameters. In the dissertation, the grinding process is regarded as an integration of all microscopic interactions, and a methodology is established for the physics based modeling. To determine the engagement condition for all micro-modes quantitatively, a virtual grinding wheel model is developed based on wheel fabrication procedure analysis and a kinematics simulation is conducted according to the operational parameters of the grinding process. A Finite Element Analysis (FEA) is carried out to study the single grain cutting under different conditions to characterize and quantify the grain-workpiece interface. Given the engagement condition on each individual grain with the workpiece from the physics-based simulation, the force, chip generation, and material plastic flow can be determined through the simulation results. Therefore, the microscopic output on each discrete point in the wheel-workpiece contact zone can be derived, and the grinding process technical output is the integrated product of all microscopic interaction output. From the perspective of process prediction and optimization, the simulation can provide the output value including the tangential force and surface texture. In terms of the microscopic analysis for mechanism study, the simulation is able to estimate the number of cutting and plowing grains, cutting and plowing force, probability of loading occurrence, which can be used as evidence for process diagnosis and improvement. A series of experiments are carried out to verify the simulation results. The simulation results are consistent with the experimental results in terms of the tangential force and surface roughness Ra for dry grinding of hardened D2 steel. The methodology enables the description of the \u27inside story\u27 in grinding processes from a microscopic point of view, which also helps explain and predict the time dependent behavior in grinding. Furthermore, the process model can be used for grinding force (or power) estimation for multiple-stage grinding cycles which includes rough, semi-finish, finish, and spark out. Therefore, the grinding process design can be carried out proactively while eliminating \u27trial and error\u27. In addition, the grinding wheel model itself can be used to guide the recipe development and optimization of grinding wheels. While the single grain micro-cutting model can be used to study the mechanism of single grit cutting under various complex conditions, it can also be used to derive the optimal parameters for specific grains or process conditions

Investigation of Material Removal Mechanism in Grinding: A Single Grit Approach

This thesis has investigated material removal mechanisms in grinding by considering single grit workpiece interaction. The investigation was performed both experimentally and using finite element simulation. Rubbing, ploughing and cutting mechanisms occurring during the grinding process were studied at the micro scale. Due to its nature the rubbing phase occurs in a very narrow region of grit-workpiece engagement and is difficult to examine under a microscope and so was investigated using FEM simulation. The ploughing mechanism was thoroughly investigated using both experimental tests and FEM simulations, and a similar trend was observed for the pile up ratio along the scratch path from the experimental tests and the FEM simulations. Ploughing and cutting mechanisms in grinding were found to be highly influenced by grit cutting edge shape, sharpness and bluntness. Cutting is the prominent mechanism when the grit cutting edge is sharp, but ploughing is more prominent when the grit cutting edge becomes flattened. In the case of multiple edges scratch formation, ploughing is dramatically increased compared to single edge scratches. Feasibility of ground surface simulation using FEM is demonstrated using multiple pass scratch formation in a cross direction. Although chip formation mechanism is developed at a relatively higher depth of cut (greater than 10 μm), at small scales down to 1 μm, FEM simulation was not a suitable method to use. To reduce the drawbacks of FEM simulation in micro scale cutting, a meshless simulation technique such as smooth particle hydrodynamics is recommended for future studies

Artificial intelligence modeling of induction contour hardening of 300M steel bar and C45 steel spur-gear

Induction hardening is a heat surface treatment technique widely employed for steel components in order to improve their fatigue life without affecting the metallurgy of the bulk material. The control of the treated components goes through the prediction and the optimization of the induction hardening process parameters. The aim of this work is to propose an approach based on artificial intelligence technique to predict the in-depth hardness profile. For this purpose, experimental tests were first carried out on 300M steel bar and C45 steel spur-gear under single and double frequencies, respectively. Intermediate variables were then generated to be used as input data. Data-driven model based on XGBoost library was finally developed. It was found that the proposed approach predicts with good agreement the hardness profiles and can be used in induction treatment process optimization

FEM-based study of precision hard turning of stainless steel 316L

This study aims to investigate chip formation and surface generation during the precision turning of stainless steel 316L samples. A Finite Element Method (FEM) was used to simulate the chipping process of the stainless steel but with only a restricted number of process parameters. A set of turning tests was carried out using tungsten carbide tools under similar cutting conditions to validate the results obtained from the FEM for the chipping process and at the same time to experimentally examine the generated surface roughness. These results helped in the analysis and understanding the chip formation process and the surface generation phenomena during the cutting process, especially on micro scale. Good agreement between experiments and FEM results was found, which confirmed that the cutting process was accurately simulated by the FEM and allowed the identification of the optimum process parameters to ensure high performance. Results obtained from the simulation revealed that, an applied feed equals to 0.75 of edge radius of new cutting tool is the optimal cutting conditions for stainless steel 316L. Moreover, the experimental results demonstrated that in contrast to conventional turning processes, a nonlinear relationship was found between the feed rate and obtainable surface roughness, with a minimum surface roughness obtained when the feed rate laid between 0.75 and 1.25 times the original cutting edge radius, for new and worn tools, respectively