Statistical Cutting Force Model for Orthogonal Cutting of Polytetrafluoroethylene (PTFE) Composites

2013 ◽  
Author(s):  
Felicia Stan ◽  
Daniel Vlad ◽  
Catalin Fetecau
Keyword(s):  
Friction Coefficient ◽  
Cutting Force ◽  
Feed Rate ◽  
Normal Force ◽  
Polynomial Regression ◽  
Orthogonal Cutting ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Tool Geometry ◽  
Force Model

This paper presents an experimental investigation of the cutting forces response during the orthogonal cutting of polytetrafluoroethylene (PTFE) and PTFE-based composites using the Taguchi method. Cutting experiments were conducted using the L27 orthogonal array and the effects of the cutting parameters (feed rate, cutting speed and rake angle) on the cutting force were analyzed using the S/N ratio response and the analysis of variance (ANOVA). Statistical models that correlate the cutting force with process variables were developed using ANOVA and polynomial regression. The variation of the apparent friction coefficient was analyzed with respect to tool geometry and the cutting process. The results indicated that cutting and thrust forces increase with increasing feed rate, and decrease with increasing rake angles from negative to positive values and increasing cutting speed. A power law relationship between the apparent friction coefficient and the normal force exerted by the chip on the tool-rake face was identified, the former decreasing with an increasing normal force.

Mechanism of Chip Deformation in Orthogonal Cutting the Wheel Steel

2008 ◽  
Vol 375-376 ◽  
pp. 26-30
Author(s):  
Kai Xue ◽  
Xiang Ming Xu ◽  
Gang Liu ◽  
Ming Chen
Keyword(s):  
Chip Formation ◽  
Feed Rate ◽  
Orthogonal Cutting ◽  
Cutting Speed ◽  
Chip Morphology ◽  
Cutting Parameters ◽  
Wheel Steel ◽  
Tool Geometry ◽  
Orthogonal Turning ◽  
On Chip

The chip formation and morphology are definitely affected by tool geometry and cutting parameters such as cutting speed, feed rate, and depth of cutting. An experiment investigation was presented to study the influence of tool geometry on chip morphology, and to clarify the effect of different cutting parameters on chip deformation in orthogonal turning the wheel steel. The result obtained in this study showed that tool geometry affected the chip morphology significantly; cutting speed was the most contributive factor in forming saw-tooth chip.

Statistical Analysis of Cutting Force, Temperature and Power of FEM Modeling when Machining Titanium Alloy

2014 ◽  
Vol 693 ◽  
pp. 358-363 ◽  
Author(s):  
Ladislav Kandráč ◽  
Ildikó Maňková ◽  
Marek Vrabeľ ◽  
Jozef Beňo ◽  
Jozef Stahovec ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Cutting Force ◽  
Feed Rate ◽  
Orthogonal Cutting ◽  
Cutting Speed ◽  
Fem Analysis ◽  
Cutting Edge ◽  
Fem Modeling ◽  
Cutting Edge Radius ◽  
Edge Radius

FEM analysis was performed on design of experiment (DoE) according to Taguchi plan L9 (34). In order to overcome the machinability issues associated with machining of Ti-6Al-4V alloy, an attempt has been made in this study to observe the effect of friction coefficient, cutting speed, feed rate and cutting edge radius and on cutting force, temperature and power in 2D orthogonal cutting process supported through out with Third Wave Systems’ AdvantEdge. The comparison between the predicted cutting force, temperature and power at varying of friction coefficient, cutting speed, feed rate and cutting edge radius are presented and discussed. Evaluation of obtained results was processed by the statistical software Minitab 16.

An Experimental Study of Cutting Force on Large Cutting Depth Turning Titanium Alloy with CBN Tool

2014 ◽  
Vol 800-801 ◽  
pp. 237-240
Author(s):  
Li Fu Xu ◽  
Ze Liang Wang ◽  
Shu Tao Huang ◽  
Bao Lin Dai
Keyword(s):  
Experimental Study ◽  
Titanium Alloy ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Depth ◽  
Cbn Tool ◽  
Cutting Experiment ◽  
Rough Turning

In this paper, the cutting experiment was used to study the influence of various cutting parameters on cutting force when rough turning titanium alloy (TC4) with the whole CBN tool. The results indicate that among the cutting speed, feed rate and cutting depth, the influence of the cutting depth is the most significant on cutting force; the next is the feed rate and the cutting speed is at least.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

Cutting Performance and Failure Mechanisms of Coated Carbide Tools in Face Milling Powder Metallurgy Nickel-Based Superalloy

2012 ◽  
Vol 497 ◽  
pp. 94-98
Author(s):  
Yang Qiao ◽  
Xiu Li Fu ◽  
Xue Feng Yang
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Failure Mechanisms ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Face Milling ◽  
Nickel Based Superalloy ◽  
Coated Carbide ◽  
Coated Carbide Tools

Powder metallurgy (PM) nickel-based superalloy is regarded as one of the most important aerospace industry materials, which has been widely used in advanced turbo-engines. This work presents an orthogonal design experiments to study the cutting force and cutting temperature variations in the face milling of PM nickel-based superalloy with PVD coated carbide tools. Experimental results show that with the increase of feed rate and depth of cut, there is a growing tendency in cutting force, with the increase of cutting speed, cutting force decreases. Among the cutting parameters, feed rate has the greatest influence on cutting force, especially when cutting speed exceeds 60m/min. With the increase of all the cutting parameters, cutting temperature increases. However the cutting temperature increases slightly as the increasing of feed rate. Tool failure mechanisms in face milling of PM nickel-based superalloy are analyzed. It is shown that the breakage and spalling on the cutting edge are the most dominate failure mechanisms, which dominates the deterioration and final failure of the coated carbide tools.

Experimental Study on Wear-Resistance of Machined Surface in High Speed Milling Aviation Aluminum Alloy

2012 ◽  
Vol 500 ◽  
pp. 117-122
Author(s):  
Xiu Li Fu ◽  
Xiao Qin Wang ◽  
Yong Zhi Pan ◽  
Yang Qiao
Keyword(s):  
Wear Resistance ◽  
Aluminum Alloy ◽  
Friction Coefficient ◽  
Surface Quality ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machined Surface ◽  
Resistance Performance

The wear-resistance performance of machined surface is an important factor in the evaluation of surface quality and precision in aerospace manufacturing industry. By using high-speed Ring-Block friction and wear machine (MRH-3), the influence of cutting parameters in milling aluminum alloy 7050-T7451 on wear-resistance of machined surface including friction coefficient and wear quantity are experimentally investigated. The wear-resistance is particularly sensitive to cutting speed and feed rate. The friction coefficient has marked drop trends as cutting speed increases. The influence of cutting speed on wear quantity is more complicated and the tendency of wear quantity was ascend in first and descend at last (v>900/min). The results show that the influence of cutting parameters on wear-resistance was also positively correlated with surface roughness and work-hardening of machined surface. The high work-hardening and surface quality had the promoting effecting on wear-resistance. The experiment and analysis results show that the machined surface by high speed cutting and lower feed rate has more superior in surface quality and wear-resistance performance comparing with conventional cutting speed.

A Parametric Optimization on Cutting Force during Laser Assisted Machining of Inconel 718 Alloy

2015 ◽  
Vol 787 ◽  
pp. 460-464 ◽  
Author(s):  
M. Vignesh ◽  
K. Venkatesan ◽  
R. Ramanujam ◽  
P. Kuppan
Keyword(s):  
Cutting Force ◽  
Feed Rate ◽  
Inconel 718 ◽  
Laser Power ◽  
Laser Cutting ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Work Piece ◽  
Conventional Machining

Inconel 718, a nickel based alloys, addressed as difficult to cut material because of hard carbide particle, hardness, work hardening and low thermal conductivity. Improving the machinability characteristics of nickel based alloys is a major anxiety in aircraft, space vehicle and other manufacturing fields. This paper presents an experimental investigation in Laser assisted turning of Inconel 718 to determine the effects of laser cutting parameters on cutting temperature and cutting forces. This nickel alloy has a material hardness at 48 HRC and machined with TICN/Al2O3/TiN tool. This is employed for the manufacture of helicopter rotor blades and cryogenic storage tanks. The experiments were conducted at One-Factor-at-a-Time.The effects of laser cutting parameters, namely cutting speed, feed rate, laser power and laser to work piece angle, on the cutting temperature and cutting force components, are critically analysed and the results are compared with unassisted machining of this alloy. The experiments are conducted by varying the cutting speed at three levels (50, 75, 100 m/min), feed rate (0.05, 0.075 0.1 mm/rev), laser power (1.25 kW, 1.5 kW, 1.75 kW) and at two level laser to work piece angle (60, 75°). At the optimal parametric combinationof laser power 1.5 kW with cutting speed of 75m/min, feed rate of 0.075 mm/min and laser to work piece angle 60°, the benefit of LAM was shown by 18%, 25% and 24% decrease in feed force (Fx), thrust force (Fy) and cutting force (Fz) as compared to those of the conventional machining. Examination of the machined surface hardness profiles showed no change under LAM and conventional machining.

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

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).

Orthogonal Cutting of Biological Soft Tissue with Single Cutting Edge

2011 ◽  
Vol 121-126 ◽  
pp. 283-287
Author(s):  
Li Ying Gao ◽  
Qin He Zhang ◽  
Ming Liu
Keyword(s):  
Soft Tissue ◽  
Cutting Force ◽  
Orthogonal Cutting ◽  
Cutting Speed ◽  
Force Model ◽  
Porcine Liver ◽  
Tissue Cutting ◽  
Cutting Model ◽  
Biological Soft Tissue ◽  
Cutting Speeds

An orthogonal cutting model for investigating indentation type cutting of soft tissue was established, and the cutting force model was constructed theoretically based on fracture mechanics. A planar biological soft tissue cutting experimental setup was designed and developed to realize soft tissue cutting. Cutting experiments using orthogonal cutting blades were performed on fresh porcine liver at different cutting speeds. It was experimentally shown that the cutting speeds and the blade rake angles have significant effects on the penetration force and cutting force. Finally, a regression equation was obtained to explain the relationship among cutting force, cutting speed, and rake angle. These findings provide new insight into the biological soft tissue cutting.

scholarly journals PREDICTION OF TANGENTIAL CUTTING FORCE IN END MILLING OF MEDIUM CARBON STEEL BY COUPLING DESIGN OF EXPERIMENT AND RESPONSE SURFACE METHODOLOGY

1970 ◽  
Vol 40 (2) ◽  
pp. 95-103 ◽  
Author(s):  
Md. Anayet Patwari ◽  
A.K.M. Nurul Amin ◽  
Waleed F. Faris
Keyword(s):  
Response Surface Methodology ◽  
Carbon Steel ◽  
Cutting Force ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Medium Carbon Steel ◽  
Depth Of Cut ◽  
Medium Carbon

The present paper discusses the development of the first and second order models for predicting the tangential cutting force produced in end-milling operation of medium carbon steel. The mathematical model for the cutting force prediction has been developed, in terms of cutting parameters cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). All the individual cutting parameters affect on cutting forces as well as their interaction are also investigated in this study. The second order equation shows, based on the variance analysis, that the most influential input parameter was the feed rate followed by axial depth of cut and, finally, by the cutting speed. Central composite design was employed in developing the cutting force models in relation to primary cutting parameters. The experimental results indicate that the proposed mathematical models suggested could adequately describe the performance indicators within the limits of the factors that are being investigated. The adequacy of the predictive model was verified using ANOVA at 95% confidence level. This paper presents an approach to predict cutting force model in end milling of medium carbon steel using coated TiN insert under dry conditions and full immersion cutting.Keywords: Tangential Cutting Forces; RSM; coated TiN; model.DOI: 10.3329/jme.v40i2.5350Journal of Mechanical Engineering, Vol. ME 40, No. 2, December 2009 95-103

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