Finite Element Modeling of Microstructural Changes in Hard Machining of SAE 8620

Caruso, Serafino; Rotella, Giovanna; Prete, Antonio Del; Umbrello, Domenico

doi:10.3390/app10010121

Cited by 3 publications

(2 citation statements)

References 24 publications

(18 reference statements)

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“…However, in dry machining, the thermal effects become more relevant compared to the effects of plastic deformation due to mechanical actions on the surface. This results in greater surface alterations at both microstructural and geometric levels [18][19][20]. Due to the high importance of the surface state in phenomena such as crack and microcrack initiation, which can affect significant properties such as fatigue resistance or corrosion [21], it is necessary to analyze the effect of the machining input variables on the machined part surface integrity.…”

Section: Introductionmentioning

confidence: 99%

Cutting Speed and Feed Influence on Surface Microhardness of Dry-Turned UNS A97075-T6 Alloy

et al. 2020

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In this work, an analysis of the cutting speed and feed influence on surface roughness and microhardness of UNS A97075-T6 alloy, turned under dry conditions, was carried out. The results were compared before and after a corrosion process. The influence of these cutting parameters on each of these variables was analyzed, as well as the possible interrelation between them. The microgeometrical deviations showed a general trend to increase with feed. However, no significant modifications were observed as a function of the cutting speed. This trend was softer after the corrosion process, due to the surface alterations produced by pitting corrosion, which resulted in higher dispersion of the experimental data. In addition, a surface microhardness increment was observed in all samples, after machining and before corrosion, regardless of the cutting parameter values. The experimental results revealed that the mechanical effects, produced by the feed, should not be neglected against the thermal effects, produced by the cutting speed, within the range of the tested cutting speed. Finally, the corrosion process negatively affected the microhardness, but it was not possible to establish a direct relationship between the cutting parameters, surface roughness, and microhardness after a corrosion process.

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Section: Introductionmentioning

confidence: 99%

Cutting Speed and Feed Influence on Surface Microhardness of Dry-Turned UNS A97075-T6 Alloy

et al. 2020

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“…For the recrystallization theory, Jafarian et al [9,10] proposed a model based on the hardness of the material, combined with the model based on the Zener-Hollomon parameter (Z-H model) to study the influence of tool micro-edges including the edge radius and chamfer angle for Inconel 718 microstructure evolution during the cutting process, especially the effect of grain size and hardness. Caruso et al [11] studied the microstructure evolution of the SAE 8620 cutting process by combining the hardness-based Johnson-Cook (J-C) material constitutive model and the Z-H model. The results indicate that the average prediction error for grain size is approximately 20%, while for surface hardness, it is 4%.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size

Zhuang

Wang

Zou³

et al. 2023

Materials

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Machining nickel-based alloys always exhibits significant work-hardening behavior, which may help to improve the part quality by building a hardened layer on the surface, while also causing severe tool wear during machining. Hence, modeling the work-hardening phenomenon plays a critical role in the evaluation of tool wear and part quality. This paper aims to propose a numerical model to estimate the work-hardening layer for a deeper understanding of this behavior, employing both recrystallization-based and dislocation-based models to cover workpieces with multiscale grain sizes. Different user routines are implemented in the finite element method to simulate the increase in hardness in the deformed area due to recrystallization or changes in the dislocation density. The validation of the proposed model is performed with both literature and experimental data for Inconel 718 with small or large grain sizes. It is found that the recrystallization-based model is more suitable for predicting the work-hardening behavior of small-grain-size Inconel 718 and the dislocation-based model is better for that of large-grain-size Inconel 718. Further, as an important type of cutting tool in machining Inconel 718, the chamfered tools with different edge geometries are employed in the simulations of machining-induced work hardening. The results illustrate that the uncut chip thickness and chamfer angle have a significant influence on the work-hardening behavior.

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Energy consumption and surface roughness maps for low and moderate speed machining of Aluminum alloy 2014: An experimental study

Shaukat,

Gohari,

Molla

2023

AIMSMATES

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<abstract> <p>The rising energy prices and soaring environmental concerns have put an immense pressure on the wide usage of machining processes. The total power consumption during machining includes the power consumed by the machine itself and the power used to remove the material from the workpiece. An accurate prediction of energy consumption during the machining process is the basis for energy reduction. In this study, the specific cutting energy and surface finish for low and moderate-speed orthogonal machining of the aluminum alloy 2014 are evaluated. The measured values for the specific cutting energy and surface roughness are presented as maps on a grid, which is based on the machining parameters including the following: (1) cutting speed and (2) undeformed chip thickness. The specific cutting energy map depicts low energy consumption values of 0.52 J/mm<sup>3</sup> for the aluminum alloy 2014 at medium speed machining. The roughness maps depict high roughness values at high cutting speeds. Both maps help in optimizing the machining process to achieve a required surface roughness with minimal energy consumption. A review of a specific cutting energy map demonstrates that energy consumption decreases by increasing the cutting speeds. The decrease in energy consumption at moderate speeds corresponds to the low cutting forces. This potentially happens as a result of thermal softening of the material caused by adiabatic heating. This subsequently leads to an increase in the machinability of the aluminum alloy 2014 at moderate cutting speeds. Furthermore, the decreasing chip thickness and increasing shear angle as a result of increasing the cutting speed confirms the increased machinability of the workpiece at moderate speeds.</p> </abstract>

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Finite Element Modeling of Microstructural Changes in Hard Machining of SAE 8620

Cited by 3 publications

References 24 publications

Cutting Speed and Feed Influence on Surface Microhardness of Dry-Turned UNS A97075-T6 Alloy

Cutting Speed and Feed Influence on Surface Microhardness of Dry-Turned UNS A97075-T6 Alloy

Simulation of Work Hardening in Machining Inconel 718 with Multiscale Grain Size

Energy consumption and surface roughness maps for low and moderate speed machining of Aluminum alloy 2014: An experimental study

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