Influence of the Nose Radius on the Machining Forces Induced during AISI-4140 Hard Turning: A CAD-Based and 3D FEM Approach

The present study investigated the performance of three ceramic inserts in terms of the micro-geometry (nose radius and cutting edge type) with the aid of a 3D finite element (FE) model. A set of nine simulation runs was performed according to three levels of cutting speed and feed rate with respect to a predefined depth of cut and tool nose radius. The yielded results were compared to the experimental values that were acquired at identical cutting conditions as the simulated ones for verification purposes. Consequently, two more sets of nine simulations each were carried out so that a total of 27 turning simulation runs would adduce. The two extra sets corresponded to the same cutting conditions, but to different cutting tools (with varied nose radius). Moreover, a prediction model was established based on statistical methodologies such as the response surface methodology (RSM) and the analysis of variance (ANOVA), further investigating the relationship between the critical parameters (cutting speed, feed rate, and nose radius) and their influence on the generated turning force components. The comparison between the experimental values of the cutting force components and the simulated ones demonstrated an increased correlation that exceeded 89%. Similarly, the values derived from the statistical model were in compliance with the equivalent FE model values due to the verified adequacy.

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CAD-Based 3D-FE Modelling of AISI-D3 Turning with Ceramic Tooling

Machines ◽

10.3390/machines9010004 ◽

2021 ◽

Vol 9 (1) ◽

pp. 4

Author(s):

Panagiotis Kyratsis ◽

Anastasios Tzotzis ◽

Angelos Markopoulos ◽

Nikolaos Tapoglou

Keyword(s):

Statistical Model ◽

Cutting Speed ◽

Depth Of Cut ◽

Fe Model ◽

Fe Modelling ◽

3D Finite Element ◽

Force Components ◽

Four Levels ◽

The Relationship ◽

Strong Agreement

In this study, the development of a 3D Finite Element (FE) model for the turning of AISI-D3 with ceramic tooling is presented, with respect to four levels of cutting speed, feed, and depth of cut. The Taguchi method was employed in order to create the orthogonal array according to the variables involved in the study, reducing this way the number of the required simulation runs. Moreover, the possibility of developing a prediction model based on well-established statistical tools such as the Response Surface Methodology (RSM) and the Analysis of Variance (ANOVA) was examined, in order to further investigate the relationship between the cutting speed, feed, and depth of cut, as well as their influence on the produced force components. The findings of this study point out an increased correlation between the experimental results and the simulated ones, with a relative error below 10% for most tests. Similarly, the values derived from the developed statistical model indicate a strong agreement with the equivalent numerical values due to the verified adequacy of the statistical model.

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Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.447-448.51 ◽

2010 ◽

Vol 447-448 ◽

pp. 51-54

Author(s):

Mohd Fazuri Abdullah ◽

Muhammad Ilman Hakimi Chua Abdullah ◽

Abu Bakar Sulong ◽

Jaharah A. Ghani

Keyword(s):

Surface Roughness ◽

Stainless Steel ◽

Surface Finish ◽

Feed Rate ◽

Cutting Speed ◽

Chip Thickness ◽

Cutting Parameters ◽

Depth Of Cut ◽

Nose Radius ◽

Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

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Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6

Al-Khwarizmi Engineering Journal ◽

10.22153/https://doi.org/10.22153/kej.2018.10.004 ◽

2018 ◽

Vol 14 (1) ◽

pp. 67-76

Author(s):

Mohanned Mohammed H. AL-Khafaji

Keyword(s):

Cutting Force ◽

Feed Rate ◽

Cutting Speed ◽

Chip Thickness ◽

Cutting Parameters ◽

Thickness Ratio ◽

Depth Of Cut ◽

Feed Force ◽

Machining Force ◽

Force Components

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).

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Experimental Investigations of Cutting Conditions Influence on Main Cutting Force and Surface Roughness Based on Chip Form Types in Cast Nylon Turning

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.110-116.3563 ◽

2011 ◽

Vol 110-116 ◽

pp. 3563-3569 ◽

Cited By ~ 1

Author(s):

Bandit Suksawat

Keyword(s):

Surface Roughness ◽

Cutting Force ◽

Feed Rate ◽

Causal Effect ◽

Cutting Speed ◽

High Speed Steel ◽

Cutting Conditions ◽

Depth Of Cut ◽

Path Coefficient ◽

Cutting Depth

This paper aims to investigate cutting conditions influence on main cutting force and surface roughness based on considered chip form types in cast nylon turning operation with single-point high speed steel cutting tool. The 75 experiments were performed by average of three levels of cutting speed, five levels of cutting depth and five levels of feed rate. The results reveal that main cutting forces were increased by an increasing of cutting speed and cutting depth for all obtained chip form types for all chip form types. The surface roughness is affected by increasing of feed rate and reduction of cutting speed for 2.3 Snarled and 4.3 Snarled chip form types. The statistical path-coefficient analysis results are shown that the main cutting force affected by cutting speed, depth of cut and feed rate with total causal effect value of 0.5537, 0.4785 and 0.1718, respectively. The surface roughness is influenced by feed rate, cutting speed and depth of cut with 0.8400, -0.2419 and-0.0711 of total causal effect value, respectively. These results are useful to perform varying cutting conditions for high quality of workpiece in cast nylon turning by control the chip form type.

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Surface Roughness Prediction Model in Machining of 34CrMo4 Steel with Several Tools Using Response Surface Methodology

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.445.90 ◽

2012 ◽

Vol 445 ◽

pp. 90-95

Author(s):

Hamed Barghikar ◽

Amin Poursafar ◽

Abbas Amrollahi

Keyword(s):

Surface Roughness ◽

Response Surface Methodology ◽

Response Surface ◽

Feed Rate ◽

Cutting Speed ◽

Depth Of Cut ◽

Nose Radius ◽

Mean Values ◽

Roughness Model ◽

34Crmo4 Steel

The surface roughness model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radius under different cutting conditions. The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels.The established equation and graphs show that the feed rate and cutting speed were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut, but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant. However, it could be seen that the first-order affect of feed rate was significant while cutting speed and depth of cut was insignificant.The predicted surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.

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Impact of Tool Geometry on Cutting Dynamics

Volume 1: 21st Biennial Conference on Mechanical Vibration and Noise, Parts A, B, and C ◽

10.1115/detc2007-35472 ◽

2007 ◽

Author(s):

Achala V. Dassanayake ◽

C. Steve Suh

Keyword(s):

Feed Rate ◽

Cutting Forces ◽

Cutting Speed ◽

Rake Angle ◽

Tool Geometry ◽

Depth Of Cut ◽

Unstable System ◽

Edge Angle ◽

Cutting Force Components ◽

Force Components

Machining stability in response to changing tool geometry is studied using a 3D turning model that considers coupled tool-workpiece dynamics subject to nonlinear regenerative cutting forces [1]. As tool geometry varies with the specified tool angles, values of tool rake angle, side cutting edge angle, and inclination angle are considered in the study as the controlled parameters. In the presented model, cutting force components in the X, Y, and Z directions vary with the variations of tool geometry, thus resulting in changes in cutting dynamics — a major feature not attainable using 1D models. It is found that tool geometry does have a significant effect on machining stability. In contrast to commonly used stability charts that are created by considering varying cutting speed and depth-of-cut (DOC), the study makes an observation that tool geometry can be a variable effective in restoring an unstable system back to stability without having to resort to changing cutting speed, feed rate or DOC.

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Effect of Cutting Parameters on Surface Texture of Flame Sprayed Coatings

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.199.396 ◽

2013 ◽

Vol 199 ◽

pp. 396-401

Author(s):

Robert Starosta

Keyword(s):

Feed Rate ◽

Cutting Tools ◽

Cutting Speed ◽

Cutting Parameters ◽

Rake Angle ◽

Depth Of Cut ◽

Nose Radius ◽

Clearance Angle ◽

Approach Angle ◽

Cutting Inserts

Coatings were turned by two tools: a) ISO 2R 2525K10, geometry and cutting parameters recommended by Messner Eutectic Castolin Company (tool angle β = 90o, approach angle κr = 45o, nose radius rε =0,8 mm, clearance angle α = 6o, rake angle γ = -5o) b) bit tool with CBN WNGA080408S01030A insert mounted in DWLNRL-2525M08 holder (cutting inserts β = 80o, approach angle κr = 95o, nose radius 0,8 mm, clearance angle α = 6o, rake angle γ = -6o). The influence of cutting speed, feed rate, depth of turning on the coating surface roughness was estimated. The following cutting parameters: cutting speed Vc = 45 214 m/min, feed rate f = 0,04 0,196 mm/rev, depth of cut ap = 0,05 0,3 mm. The lowest value of the roughness Ra = 0,5μm of the coatings were obtained by using cutting tools and parameters and bit tool: Vc = 214 m/min, f = 0,06 mm/rev, ap = 0,3 mm.

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Predicting the Effects of Cutting Parameters and Tool Geometry on Hard Turning Process Using Finite Element Method

Journal of Manufacturing Science and Engineering ◽

10.1115/1.4004611 ◽

2011 ◽

Vol 133 (4) ◽

Cited By ~ 24

Author(s):

Xueping Zhang ◽

Shenfeng Wu ◽

Heping Wang ◽

C. Richard Liu

Keyword(s):

Finite Element ◽

Feed Rate ◽

Hard Turning ◽

Tangential Force ◽

Cutting Speed ◽

Chip Morphology ◽

Rake Angle ◽

Fe Model ◽

Turning Process ◽

Nose Radius

To explore the effects of cutting speed, feed rate and rake angle on chip morphology transition, a thermomechanical coupled orthogonal (2-D) finite element (FE) model is developed, and to determine the effects of tool nose radius and lead angle on hard turning process, an oblique (3-D) FE model is further proposed. Three one-factor simulations are conducted to determine the evolution of chip morphology with feed rate, rake angle, and cutting speed, respectively. The chip morphology evolution from continuous to saw-tooth chip is described by means of the variations of chip dimensional values, saw-tooth chip segmental degree and frequency. The results suggest that chip morphology transits from continuous to saw-tooth chip with increasing feed rate and cutting speed, and changing a tool’s positive rake angle to negative rake angle. There exists a critical cutting speed at which the chip morphology transfers from continuous to saw-tooth chip. The saw-tooth chip segmental frequency decreases as the feed rate and the tool negative rake angle value increases; however, it increases almost linearly with the cutting speed. The larger negative rake angle, the larger feed rate and higher cutting speed dominate saw-tooth chip morphology while positive rake angle, small feed rate and low cutting speed combine to determine continuous chip morphology. The 3-D FE model considers tool nose radii of 0.4 mm and 0.8 mm, respectively, with tool lead angels of 0 deg and 7 deg. The model successfully simulates 3-D saw-tooth chip morphology generated by periodic adiabatic shear and demonstrates the continuous and saw-tooth chip morphology, chip characteristic line and the material flow direction between chip-tool interfaces. The predicted chip morphology, cutting temperature, plastic strain distribution, and cutting forces agree well with the experimental data. The oblique cutting process simulation reveals that a bigger lead angle results in a severer chip deformation, the maximum temperature on the chip-tool interface reaches 1289 deg, close to the measured average temperature of 1100 deg; the predicted average tangential force is 150N, with 7% difference from the experimental data. When the cutting tool nose radius increases to 0.8 mm, the chip’s temperature and strain becomes relatively higher, and average tangential force increases 10N. This paper also discusses reasons for discrepancies between the experimental measured cutting force and that predicted by finite element simulation.

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Numerical Investigation of the Slot Up Milling of Ti-6Al-4V

Volume 4: Processes ◽

10.1115/msec2018-6498 ◽

2018 ◽

Author(s):

Xingbang Chen ◽

Ashutosh Khatri ◽

J. Ma ◽

Muhammad P. Jahan

Keyword(s):

Finite Element Method ◽

Cutting Force ◽

Numerical Investigation ◽

Strong Influence ◽

Cutting Speed ◽

Cutting Conditions ◽

Depth Of Cut ◽

Slot Milling ◽

Cutting Force Components ◽

Force Components

In this paper, numerical investigation of the effects of cutting conditions in slot up milling of Ti-6Al-4V is conducted using Finite Element Method (FEM). Experiments are conducted to validate the FEM models. The validated models are then used to predict the cutting force components when different cutting conditions are applied. It is found that cutting speed, feed rate, and depth of cut have strong influence on cutting force components and tool temperature. This research provides insightful guidance for selecting optimal cutting conditions for slot milling of Ti-6Al-4V.

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A Method to Determine the Minimum Chip Thickness during Longitudinal Turning

Micromachines ◽

10.3390/mi11121029 ◽

2020 ◽

Vol 11 (12) ◽

pp. 1029

Author(s):

Michal Skrzyniarz

Keyword(s):

Cutting Speed ◽

Chip Thickness ◽

Cutting Conditions ◽

Depth Of Cut ◽

Nose Radius ◽

Minimum Chip Thickness ◽

Edge Radius ◽

Longitudinal Turning ◽

Workpiece Interaction ◽

Elastic And Plastic Deformation

Micromachining, which is used for various industrial purposes, requires the depth of cut and feed to be expressed in micrometers. Appropriate stock allowance and cutting conditions need to be selected to ensure that excess material is removed in the form of chips. To calculate the allowance, it is essential to take into account the tool nose radius, as this cutting parameter affects the minimum chip thickness. Theoretical and numerical studies on the topic predominate over experimental ones. This article describes a method and a test setup for determining the minimum chip thickness during turning. The workpiece was ground before turning to prevent radial runout and easily identify the transition zone. Contact and non-contact profilometers were used to measure surface profiles. The main aim of this study was to determine the tool–workpiece interaction stages and the cutting conditions under which material was removed as chips. Additionally, it was necessary to analyze how the feed, cutting speed, and edge radius influenced the minimum chip thickness. This parameter was found to be dependent on the depth of cut and feed. Elastic and plastic deformation and ploughing were observed when the feed rate was lower than the cutting edge radius.

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