A Finite Element Modeling Prediction in High Precision Milling Process of Aluminum 6082-T6

Davoudinejad, Ali; Doagou-Rad, Saeed; Tosello, Guido

doi:10.1007/s41871-018-0026-7

Cited by 7 publications

(2 citation statements)

References 31 publications

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“…In addition, these methods validate and support experimental studies and play a major role in determining solution sensitivity, effective parameters, and positive and negative factors on the problem (Shetty, Kumar, Mallagi, and Keni, 2021;Bolar, Das, and Joshi, 2018;Yılmaz, Dilipak, Sarıkaya, Yılmaz, and Özdemir, 2014). In many studies, analysis of variance (ANOVA), finite element method (FEM), linear and multiple regression models, Taguchi, ANN (artificial neural networks) and RSM (response surface method) methods were preferred (Yadav, 2021;Çiftçi and Gökçe, 2019;Davoudinejad, Doagou-Rad, and Tosello, 2018;Hazir, Erdinler, and Koc, 2018;Kumar, 2018;Chandrasekaran and Payton, 2013).…”

Section: Introductionmentioning

confidence: 99%

Investigating Cutting Force and Cutting Power When Turning Aa6082-T4 Alloy at Cutting Depths Smaller Than Tool Nose Radius

AYDIN

2023

Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

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Aluminum alloys are widely preferred engineering materials in the manufacturing industry due to their high formability, good mechanical strength, and low density. Machining problems in aluminum alloys include built-up-edge formation, chip rupturing, and low surface quality, particularly in the 6xxx series due to the high Si content in the machining area. The aim of this study was to investigate the influence of cutting depth smaller than the tool corner radius, and various cutting parameters on cutting force and cutting power in machining AA6082-T4 alloy. In this context, the Johnson-Cook material model was established for AA6082-T4 alloy, and machining behaviors in terms of cutting force, and cutting power were investigated by performing finite element method (FEM) analyses using a full factorial design and variance analyses with different machining parameters. In conclusion, the lowest cutting forces were achieved with a cutting depth of 0.3 mm and a feed of 0.1 mm/rev, and the lowest cutting power was obtained with a cutting speed of 300 m/min, a cutting depth of 0.3 mm, and a feed of 0.1 mm/rev. In addition, the most effective machining parameters have been determined as cutting depth with a ratio of 91.74% for cutting force and cutting speed with a ratio of 33.13% for cutting power based on the results of variance and regression analysis.

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Section: Introductionmentioning

confidence: 99%

Investigating Cutting Force and Cutting Power When Turning Aa6082-T4 Alloy at Cutting Depths Smaller Than Tool Nose Radius

AYDIN

2023

Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

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“…The geometry of the tools is defined in the ISO 3002-1 standard [3]. In addition, the knowledge of the geometry of microtools is the key for the development of new models for the prediction and interpretation of the chip formation process [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

3D Identification of Face and Flank in Micro-mills for Automatic Measurement of Rake Angle

Petrò

Moroni

2020

Nanomanuf Metrol

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In an Industry 4.0 context, to each object a "digital twin" is associated, which is a virtual counterpart of the object itself. In the case of a tool this includes, together with its material and manufacturing information, its solid geometry. Tool geometry knowledge is fundamental to enable effective tool management, manufacturing verification, and tooling simulation. If for tool management, the conventional 2D presetting is sufficient, tooling simulation and tool manufacturing verification require a complete 3D characterization. This is particularly true in the case of the microtools: the process of micro-chip formation is still a research subject.Although the 3D geometry of tool is well established in the ISO 3002 series of standard, only recently 3D measurement of tools has been made possible by new measuring systems. Still, tool geometry verification requires a lot of human intervention.This paper aims at setting the base for the automatic analysis point mesh scanned on the whole surface of tools, and in particular microtools.The first step for doing this is the identification of the active surfaces of the tool, that is the face and the flank plus the cutting edge. The identification of these geometric features is in general possible thanks to their specific characteristics: in particular, the cutting edge is characterized by a high curvature, and it separates the face from the flank. This paper considers cylindrical micro end-mills as a first example of an approach that can be extended to in principle any kind of tool. The cylindrical helix characterizing the cutting edge is the key geometry to be considered in the development of the specific method. Once the tool features (face, flank, and cutting edge) have been separated, of the tool angles, for instance, can be estimated. As first angle to study, the rake angle has been selected. The approach will be validated on simulated data and on real scans of micro-tools.

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Effects of Edge Radius and Coating Thickness on the Cutting Performance of AlCrN-Coated Tool

Malekan,

Ilvig,

Aghababaei

2024

Int. J. Precis. Eng. Manuf.

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High-speed machining is a practical way to attain high productivity with lower costs. Under this condition, the tool geometry needs to be optimized to sustain high cutting forces and temperatures. The sharpness of the cutting edge and the coating thickness (CT) are two key parameters that affect the tool’s performance. While a sharp edge eases the cutting process, it causes a high stress concentration, which increases the wear rate and eventual edge fracture. In this study, we use a combination of finite element simulations and experimental testing to evaluate the effects of CT ( 1–3 μm), edge radius ($$r_{\beta }$$ r β , 6–15 μm), and coefficient of friction ($$\upmu = 0 - 0.2$$ μ = 0 - 0.2 ) on the stress distribution at the cutting edge. Our simulations showed that the larger the CT, the higher the stress magnitude inside the coating, but the lower the maximum stress depth percentile. Considering an industrial case of cutting steel workpieces using AlCrN-coated tungsten carbide tools under given cutting parameters, our simulations suggested an optimum CT of 3 μm. By manufacturing a series of milling tools with different CTs and edge radii, we validated the simulation results using a set of well-controlled milling experiments. Finally, the edge radius should be selected considering the size of rake/flank angle mainly to control stress distribution over the cutting edge.

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A Finite Element Modeling Prediction in High Precision Milling Process of Aluminum 6082-T6

Cited by 7 publications

References 31 publications

Investigating Cutting Force and Cutting Power When Turning Aa6082-T4 Alloy at Cutting Depths Smaller Than Tool Nose Radius

Investigating Cutting Force and Cutting Power When Turning Aa6082-T4 Alloy at Cutting Depths Smaller Than Tool Nose Radius

3D Identification of Face and Flank in Micro-mills for Automatic Measurement of Rake Angle

Effects of Edge Radius and Coating Thickness on the Cutting Performance of AlCrN-Coated Tool

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