Finite Element Modeling and Validation of Chip Segmentation in Machining of AISI 1045 Steel

Devotta, Ashwin Moris; Beňo, Tomáš; Siriki, Ravendra; Löf, Ronnie; Eynian, Mahdi

doi:10.1016/j.procir.2017.03.259

Cited by 12 publications

(6 citation statements)

References 15 publications

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“…In the open literature [2], the machining of AISI 1045 steel was simulated using Abaqus-FEM package to detect the optimum parameters (i.e., cutting forces, feed rate and cutting depth) against coated cutting tools made of carbide coatings. To better predict machining performance, Devotta et al [3] investigated the effect of rake angle on chip segmentation. In the experimental routine, the behavior of tool–chip interface was studied by [4] considering uncoated tungsten inserts.…”

Section: Introductionmentioning

confidence: 99%

Towards Optimization of Machining Performance and Sustainability Aspects when Turning AISI 1045 Steel under Different Cooling and Lubrication Strategies

et al. 2019

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In this work, an extensive analysis has been presented and discussed to study the effectiveness of using different cooling and lubrication techniques when turning AISI 1045 steel. Three different approaches have been employed, namely dry, flood, and minimum quantity lubrication based nanofluid (MQL-nanofluid). In addition, three multi-objective optimization models have been employed to select the optimal cutting conditions. These cases include machining performance, sustainability effectiveness, and an integrated model which covers both machining outputs (i.e., surface roughness and power consumption) and sustainability aspects (carbon dioxide emissions and total machining cost). The results provided in this work offer a clear guideline to select the optimal cutting conditions based on different scenarios. It should be stated that MQL-nanofluid offered promising results through the three studied cases compared to dry and flood approaches. When considering both sustainability aspects and machining outputs, it is found that the optimal cutting conditions are cutting speed of 147 m/min, depth of cut of 0.28 mm and feed rate of 0.06 mm/rev using MQL-nanofluid. The three studied multi-objective optimization models obtained in this work provide flexibility to the decision maker(s) to select the appropriate cooling/lubrication strategy based on the desired objectives and targets, whether these targets are focused on machining performance, sustainability effectiveness, or both. Thus, this work offers a promising attempt in the open literature to optimize the machining process from the performance–sustainability point of view.

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Section: Introductionmentioning

confidence: 99%

Towards Optimization of Machining Performance and Sustainability Aspects when Turning AISI 1045 Steel under Different Cooling and Lubrication Strategies

et al. 2019

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“…17 and 18 were employed to calculate the shear angle (φ) and chip compression ratio (ζ) using the simulated data [34][35][36]. Several researchers have incorporated similar methodology to utilize experimental and simulated data for machining performance evaluation [24,27,[37][38][39].…”

Section: Effect On Chip Compression Ratio Shear Angle and Contact Lengthmentioning

confidence: 99%

Machinability analysis of dry and liquid nitrogen–based cryogenic cutting of Inconel 718: experimental and FE analysis

Pervaiz

Kannan

Anwar

et al. 2021

Int J Adv Manuf Technol

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Inconel 718 is famous for its applications in the aerospace industry due to its inherent properties of corrosion resistance, wear resistance, high creep strength, and high hot hardness. Despite the favorable properties, it has poor machinability due to low thermal conductivity and high hot hardness. To limit the influence of high cutting temperature in the cutting zone, application of cutting flood is recommended during the cutting operation. Cryogenic cooling is the recommended method when machining Inconel 718. However, there is very limited literature available when it comes to the numerical finite element modeling of the process. This current study is focused on the machinability analysis of Inconel 718 using numerical approach with experimental validations. Dry and cryogenic cooling methods were compared in terms of associated parameters such as chip compression ratio, shear angle, contact length, cutting forces, and energy consumption for the primary and secondary deformation zones. In addition, parameters related to chip morphology were also investigated under both lubrication methods. Chip formation in cryogenic machining was well captured by the finite element assisted model and found in good agreement with the experimental chip morphology. Both experimental and numerical observations revealed comparatively less chip compression ratio in the cryogenic cooling with larger value of shear plane angle. This results in the smaller tool–chip contact length and better comparative lubrication.

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“…As these experiments do not cover every condition of strain and temperature, the approximations made are an important source of errors. Rupture of the material is modelled by a damage model as in Equation ( 5) (Devotta, Beno, Siriki, Löf, & Eynian, 2017), which takes into consideration the accumulation of plastic deformation in relation to the strain at failure Ɛ which is temperature dependent, as in Equation ( 6).…”

Section: Fem Modelling and Analysismentioning

confidence: 99%

The effect of mesh parameters on computational cost and results in simulation of milling in Inconel 718

et al. 2021

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The Finite Element Method analysis of machining processes has become a ubiquitous feature to the area, however, there sometimes occur considerable deviations between experimental and simulated results due to the inherent complexity of the process. The basis for such may conceivably be related to imprecisions in the material and friction modelling, besides improper setup of mesh parameters. Elements should be small enough to allow for the proper representation of the chip formation, but taking into account that the computational time increases accordingly with mesh downsizing. Simulations of the milling process of Inconel 718 were conducted using the software Thirdwave AdvantEdge under different cutting conditions for three different meshes. Power and temperature output were compared to experimental results, most of which were measured via Hall-effect sensors and thermographic camera, respectively. The tool cutting edge radius was found to be an important factor and was estimated using Scanning Electron Microscope images. The influence of the finite element mesh size was higher for harsher cutting conditions, with effects felt on machining power only. In this case, finer mesh produced results that showed a higher agreement with experimental data, but at higher computational cost as shown by analysis of elapsed processing time. Although errors higher than 40% were observed, power and temperature trends from simulations were always in accordance with that found in experimental tests. Comparisons with experimental data from other studies showed the errors tend to grow for higher feed and cutting speed, which indicates the constitutive model of the material is more adequate for softer machining conditions. Simulation time seemed to be exponentially proportional to the inverse of minimum element size, and measured values might serve as a reference for other users.

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Finite Element Modeling and Validation of Chip Segmentation in Machining of AISI 1045 Steel

Cited by 12 publications

References 15 publications

Towards Optimization of Machining Performance and Sustainability Aspects when Turning AISI 1045 Steel under Different Cooling and Lubrication Strategies

Towards Optimization of Machining Performance and Sustainability Aspects when Turning AISI 1045 Steel under Different Cooling and Lubrication Strategies

Machinability analysis of dry and liquid nitrogen–based cryogenic cutting of Inconel 718: experimental and FE analysis

The effect of mesh parameters on computational cost and results in simulation of milling in Inconel 718

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