scholarly journals CNC Edge Finishing of Granite: Effect of Machining Conditions on Part Quality, Cutting Forces, and Particle Emissions

Materials ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6496
Author(s):  
Haithem Bahri ◽  
Victor Songmene ◽  
Jules Kouam ◽  
Agnes Marie Samuel ◽  
Fawzy-Hosny Samuel
Keyword(s):  
Cutting Forces ◽  
Ultrafine Particles ◽  
Fine Particles ◽  
Health And Safety ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Particle Emissions ◽  
Part Quality ◽  
Competitive Prices ◽  
Edge Finishing

Edge finishing is a shaping process that is extremely important in the granite and marble processing industries. It does not only shape the edge but also makes it shiny and durable. However, this process generates dust (fine and ultrafine particles) that can have a significant impact on air quality in the workshop and can put workers’ health at risk. While environmental requirements and occupational health and safety regulations are becoming increasingly stringent, at the same time, industries must continue to produce quality parts at competitive prices. The purpose of this study was to examine the surface quality, the cutting forces, and the emission of fine (FP) and ultrafine (UFP) particles during wet and dry edge finishing of granite edges as a function of the machining parameters and abrasive grit sizes. Three machining operations were investigated: roughing, semi-finishing, and finishing, using diamond abrasives (with grit sizes 45, 150, 300, 600, 1500, and 3000). The experiments were carried out on two granites, one being black and the other white. The tested spindle speeds ranged from 1500 rpm to 3500 rpm and the feed rates from 500–1500 mm/min. It was found that roughing operations produce more fine particles while finishing operations produce more ultrafine particles. These particle emissions, as well as the part quality and the cutting forces are strongly dependent on cutting speed and on the grit size of the abrasive used.

Study on Fractal Characterization Laws of Cutting Force in CNC Turning Aeronautic Aluminium Alloy 7075-T651

2017 ◽  
Vol 748 ◽  
pp. 224-228 ◽  
Author(s):  
Bao Liang Xing ◽  
Jing Wang ◽  
Hui Ying Cao ◽  
Shu Zhong Zhang ◽  
Wei Wei ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Aluminium Alloy ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Fractal Dimensions ◽  
Feed Speed ◽  
Machining Parameters ◽  
Cutting Depth ◽  
Main Effect

Based on the experiment of turning aluminium alloy (7075-T651), the relations between the fractal dimensions of cutting forces with machining parameters are studied. Cutting speed, feed speed and cutting depth are considered as the process parameters. The cutting force in turning aluminium alloy operation are measured and the fractal dimension are calculated using the algorithm of correlation dimension. From main effect plots the fractal dimensions of three directions of cutting forces are reduced with the increase of cutting speed, increased with the increase of cutting depth and insignificant with the increase of feed speed. The mathematic models of fractal dimension of cutting force are developed using response surface methodology (RSM). The results of the ANOVA show that cutting speed and cutting depth have remarkable influence to fractal dimension Dx, Dy and Dz.

Fractal Characterization Analysis in CNC Milling Aluminium Alloy

2017 ◽  
Vol 748 ◽  
pp. 212-217 ◽  
Author(s):  
Zheng Mei Zhang ◽  
Bao Liang Xing ◽  
Jing Wang ◽  
Hui Ying Cao ◽  
Shao Hua Li
Keyword(s):  
Fractal Dimension ◽  
Aluminium Alloy ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Fractal Dimensions ◽  
Feed Speed ◽  
Machining Parameters ◽  
Cnc Milling ◽  
Cutting Depth

Based on the experiment of milling aluminium alloy (7075-T651), the relations between the fractal dimensions of cutting forces with machining parameters are studied. Cutting speed, feed speed and cutting depth are considered as the process parameters. The cutting force in milling aluminium alloy operation are measured and the fractal dimension are calculated using the algorithm of correlation dimension. From main effect plots the fractal dimensions of three directions of cutting forces are reduced with the increase of cutting speed and increased with the increase of feed speed and cutting depth. The mathematic models of fractal dimension of cutting force are developed using response surface methodology (RSM). The results of the ANOVA show that feed speed and cutting depth have remarkable influence to fractal dimension Dx and Dy, cutting speed and feed speed for Dz.

Cutting forces analysis of micro-milling process on Inconel 718 – a finite element approach

2020 ◽  
Vol 11 (02) ◽  
pp. 2050011
Author(s):  
Padmaja Tripathy ◽  
Kalipada Maity
Keyword(s):  
Finite Element ◽  
Cutting Forces ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Fem Analysis ◽  
Milling Process ◽  
Machining Process ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents a modeling and simulation of micro-milling process with finite element modeling (FEM) analysis to predict cutting forces. The micro-milling of Inconel 718 is conducted using high-speed steel (HSS) micro-end mill cutter of 1mm diameter. The machining parameters considered for simulation are feed rate, cutting speed and depth of cut which are varied at three levels. The FEM analysis of machining process is divided into three parts, i.e., pre-processer, simulation and post-processor. In pre-processor, the input data are provided for simulation. The machining process is further simulated with the pre-processor data. For data extraction and viewing the simulated results, post-processor is used. A set of experiments are conducted for validation of simulated process. The simulated and experimental results are compared and the results are found to be having a good agreement.

scholarly journals Effects of Machining Parameters on the Quality in Machining of Aluminium Alloys Thin Plates

Metals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 927 ◽  
Author(s):  
Irene Del Sol ◽  
Asuncion Rivero ◽  
Antonio J. Gamez
Keyword(s):  
Cutting Forces ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Thin Plates ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Final Thickness ◽  
Machined Parts ◽  
Chemical Milling ◽  
Skin Panels

Nowadays, the industry looks for sustainable processes to ensure a more environmentally friendly production. For that reason, more and more aeronautical companies are replacing chemical milling in the manufacture of skin panels and thin plates components. This is a challenging operation that requires meeting tight dimensional tolerances and differs from a rigid body machining due to the low stiffness of the part. In order to fill the gap of literature research on this field, this work proposes an experimental study of the effect of the depth of cut, the feed rate and the cutting speed on the quality characteristics of the machined parts and on the cutting forces produced during the process. Whereas surface roughness values meet the specifications for all the machining conditions, an appropriate cutting parameters selection is likely to lead to a reduction of the final thickness deviation by up to 40% and the average cutting forces by up to a 20%, which consequently eases the clamping system and reduces machine consumption. Finally, an experimental model to control the process quality based on monitoring the machine power consumption is proposed.

scholarly journals Machinability, Modelling and Statistical Analysis of In-Situ Al–Si–TiB2 Composites

2019 ◽  
Vol 3 (1) ◽  
pp. 28 ◽  
Author(s):  
Jimmy Karloopia ◽  
Shaik Mozammil ◽  
Pradeep Jha
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Tool Wear ◽  
Cutting Forces ◽  
Elevated Temperatures ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Conventional Machining

Aluminum and its alloys have numerous applications in manufacturing, aerospace, and automotive industries. At elevated temperatures, they start to fail in fulfilling their roles and functions. Aluminum-based metal matrix composites (MMCs) are good alternatives for metal and alloys due to their excellent properties. However, the conventional machining of several composites shows complications for a number of reasons, such as high tool wear, poor surface roughness, high machining cost, cutting forces, etc. Numerous studies have already been conducted on the machinability of various MMCs, but the machinability of Al–Si–TiB2 composite is still not well studied. It is of utmost importance that several process parameters of conventional machining are precisely controlled as well as optimized. In this study an effort was made to optimize input parameters such as cutting speed, depth of cut, and feed to obtain well-finished final components with the minimum cutting force and tool wear. These progressions are involved with multiple response characteristics, therefore the exploration of an appropriate multi-objective optimization technique was indeed essential. The performance characteristics of cutting forces and surface roughness were considered for optimization of the machining parameters. Analysis of variance (ANOVA) was employed for the optimization and statistical analysis.

scholarly journals Prediction of Cutting Force in Turning Process by Using Artificial Neural Network

2020 ◽  
Vol 16 (2) ◽  
pp. 34-46
Author(s):  
Marwa Qasim Ibraheem
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Artificial Neural Network ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Operation ◽  
Artificial Neural

        Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samples of experimental data were used, including nineteen to train the network. Moreover six other experimental tests were implemented to test the network. The study concludes that ANN was a dependable and precise method for predicting machining parameters in CNC turning operation.

scholarly journals Analysis of Surface Roughness and Cutting Forces in Hard Turning of 42CrMo4 Steel using Taguchi and RSM Method

Mechanika ◽  
2020 ◽  
Vol 26 (3) ◽  
pp. 231-241 ◽  
Author(s):  
Mustafa ÖZDEMİR ◽  
Mehmet Tuncay KAYA ◽  
Hamza Kemal AKYILDIZ
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Forces ◽  
Tangential Force ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Radial Force ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Feed Force

In this study, effects of cutting speed (V), feed rate (f), depth of cut (a) and tool tip radius (R) on  surface roughness (Ra, Rz, and Rt) and cutting forces (radial force (Fx), tangential force (Fy), and feed force (Fz)) in hard finish turning processes of hardened 42CrMo4 (52 HRC) material was investigated experimentally. Taguchi’s mixed level parameter design (L18) is used for the experimental design (2x1,3x3). The signal-to-noise ratio (S/N) was used in the evaluation of test results.  By using Taguchi method, cutting parameters giving optimum surface roughness and cutting forces were determined. Regression analyses are applied to predict surface roughness and cutting forces. Analysis of variance (ANOVA) is used to determine the effects of the machining parameters on surface roughness and cutting forces. According to ANOVA analysis, the most important cutting parameters were found to be feed rate for surface roughness and depth of cut among cutting forces.  By conducting validation experiments, optimization was seen to be applied successfully.

Experimental and Numerical Machining of AA 5083

2011 ◽  
Vol 189-193 ◽  
pp. 4419-4424
Author(s):  
Behnam Davoodi ◽  
Mohammad Bagher Momeni ◽  
Mohammad Reza Eslami
Keyword(s):  
Finite Element ◽  
Finite Element Modeling ◽  
Chip Formation ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Simulation Software ◽  
Constitutive Law ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Element Modeling

The experimental machining and finite element modeling of 2D turning of AA5083 is presented. The ABAQUS/Explicit machining simulation software is applied for the finite element modeling. The experimental orthogonal machining for were conducted to investigate the effects of various machining parameters on chip morphology, machined surface condition, and resulting cutting forces. The measured cutting forces was compared to finite element modeling results with good agreement. The effects of cutting speed and rack angle of tool cutting factor for productivity in AA5083 machining, depth of cut, on the peak tool temperature are investigated. 2D Finite Element Model (FEM) of chip formation process, set up with an Arbitrary Lagrangian-Eulerian (ALE) formulation, proposed in the software ABAQUS/Explicit .the thermo-viscoplastic behavior of the workpiece material is modeled by the Johnson-Cook (JC) constitutive law. This study explores the use of experimental and finite element modeling to study the cutting force. Results of this research help to guide the design of new cutting tool materials and coatings and the studies of chip formation to further advance the productivity of AA5083 machining.

Experimental Study on Fractal Laws of Cutting Force for Machining Irregular Surface of Granite

2013 ◽  
Vol 797 ◽  
pp. 214-219
Author(s):  
Jin Sheng Zhang ◽  
Zheng Mei Zhang ◽  
Ming Wei Ding ◽  
Huai Chao Wang ◽  
Zhi Wang
Keyword(s):  
Fractal Dimension ◽  
Cutting Force ◽  
Cutting Forces ◽  
Orthogonal Experiment ◽  
Cutting Speed ◽  
Fractal Dimensions ◽  
Feed Speed ◽  
Machining Parameters ◽  
Irregular Surface ◽  
Cutting Depth

Based on orthogonal experiment of machining the irregular surface of Wulian red granite (G3768) with diamond profiling wheel, the relations between the fractal dimensions of cutting forces with machining parameters are studied. Cutting speed, feed speed and cutting depth are considered as the process parameters. The cutting force in machining granite operation are measured and the fractal dimension are calculated using using the algorithm of correlation dimension. From main effect plots the fractal dimensions of three directions of cutting forces are reduced with the increase of cutting speed and increased with the increase of feed speed and cutting depth. The mathematic models of fractal dimension of cutting force are developed by analysis of regression. The results of the ANOVA show that cutting speed and feed speed have remarkable influence to fractal dimensionDx,DyandDz.

scholarly journals Multiple Regression Prediction Model for Cutting Forces in Turning Carbon-Reinforced PEEK CF30

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Francisco Mata ◽  
Elena Beamud ◽  
Issam Hanafi ◽  
Abdellatif Khamlichi ◽  
Abdallah Jabbouri ◽  
...  
Keyword(s):  
Cutting Forces ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Industrial Applications ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Quadratic Regression ◽  
Turning Operations ◽  
Dry Conditions ◽  
Full Factorial

Among the thermoplastic polymers available, the reinforced polyetheretherketone with 30% of carbon fibres (PEEK CF 30) demonstrates a particularly good combination of strength, rigidity, and hardness, which prove ideal for industrial applications. Considering these properties and potential areas of application, it is necessary to investigate the machining of PEEK CF30. In this study, response surface methodology was applied to predict the cutting forces in turning operations using TiN-coated cutting tools under dry conditions where the machining parameters are cutting speed ranges, feed rate, and depth of cut. For this study, the experiments have been conducted using full factorial design in the design of experiments (DOEs) on CNC turning machine. Based on statistical analysis, multiple quadratic regression model for cutting forces was derived with satisfactory -squared correlation. This model proved to be highly preferment for predicting cutting forces.

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