Improvement of cutting force and material removal rate for disc milling TC17 blisk tunnels using GRA–RBF–PSO method

2019 ◽  
Vol 233 (16) ◽  
pp. 5556-5567
Author(s):  
Nan Zhang ◽  
Yaoyao Shi
Keyword(s):  
Cutting Force ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Rbf Neural Network ◽  
Cutting Speed ◽  
Pso Algorithm ◽  
Milling Process ◽  
Aero Engines ◽  
Cutting Height

Blisk is a key component of new aero-engines. To improve machining efficiency, disc milling is used for roughing blisk tunnels. The multi-objective optimization is employed to optimize disc milling process. In this study, an integration-based approach that used grey relational analysis (GRA) coupled with radial basis function (RBF) neural network and particle swarm optimization (PSO) algorithm is applied to solve the optimization problem. To achieve smaller cutting force and greater material removal rate (MRR), the appropriate cutting speed, feed rate per tooth, and cutting height needed to be determined. A hybrid experiment scheme of three factors–five levels is carried out to generate data sample. Results of verified experiments indicate that GRA–RBF–PSO approach can improve performance better than original GRA.

Research on Microscopic Grain-Workpiece Interaction in Grinding through Micro-Cutting Simulation, Part 2: Factorial Study

2009 ◽  
Vol 76-78 ◽  
pp. 15-20 ◽  
Author(s):  
Lan Yan ◽  
Xue Kun Li ◽  
Feng Jiang ◽  
Zhi Xiong Zhou ◽  
Yi Ming Rong
Keyword(s):  
Cutting Force ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Shear Angle ◽  
Depth Of Cut ◽  
Specific Cutting Force ◽  
Single Grain

The grinding process can be considered as micro-cutting processes with irregular abrasive grains on the surface of grinding wheel. Single grain cutting simulation of AISI D2 steel with a wide range of cutting parameters is carried out with AdvantEdgeTM. The effect of cutting parameters on cutting force, chip formation, material removal rate, and derived parameters such as the specific cutting force, critical depth of cut and shear angle is analyzed. The formation of chip, side burr and side flow is observed in the cutting zone. Material removal rate increases with the increase of depth of cut and cutting speed. Specific cutting force decreases with the increase of depth of cut resulting in size effect. The shear angle increases as the depth of cut and cutting speed increase. This factorial analysis of single grain cutting is adopted to facilitate the calculation of force consumption for each single abrasive grain in the grinding zone.

EXPERIMENTAL ANALYSIS, STATISTICAL MODELING AND OPTIMIZATION OF EFFECTIVE PARAMETERS ON SURFACE QUALITY IN CORTICAL BONE MILLING PROCESS

2020 ◽  
Vol 20 (04) ◽  
pp. 1950078
Author(s):  
MAHDI QASEMI ◽  
M-MORAD SHEIKHI ◽  
MOJTABA ZOLFAGHARI ◽  
VAHID TAHMASBI
Keyword(s):  
Surface Quality ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Milling Process ◽  
Artificial Joint ◽  
Effective Parameters ◽  
Tool Diameter

Knee joint surgery for artificial joint replacement is common in orthopedic surgeries. In this operation, there is a need to prepare the surface of the cortical bone for mounting the artificial joint. Therefore, milling process is frequently performed. Since the surgeon should be careful not to hurt bone tissue and neurons and also minimize waste of blood, the operation should be performed in the shortest possible time. This study, for the first time, focuses on modeling and optimization of effective parameters of bone milling including cutting speed, feed rate and tool diameter on surface roughness and material removal rate using response surface method. Results showed that in order to achieve maximum surface quality, minimum feed rate, maximum tool diameter and down milling procedure should be selected. On the other hand, the maximum material removal rate coincides with maximum feed rate and tool diameter. Therefore, cutting speed of 3000[Formula: see text]rpm, feed rate of 50[Formula: see text]mm/min, tool diameter of 5[Formula: see text]mm and down milling procedure can satisfy both high surface quality and high material removal rate.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

Performance Analysis of Trihexyltetradecylphosphonium Chloride Ionic Fluid under MQL Condition in Hard turning

2020 ◽  
Vol 17 (1) ◽  
pp. 7629-7647
Author(s):  
A. Pandey ◽  
R. Kumar ◽  
A. K. Sahoo ◽  
A. Paul ◽  
A. Panda
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Coconut Oil ◽  
Chip Morphology ◽  
Weight Fraction ◽  
Cutting Fluid ◽  
Depth Of Cut

The current research presents an overall performance-based analysis of Trihexyltetradecylphosphonium Chloride [[CH3(CH2)5]P(Cl)(CH2)13CH3] ionic fluid mixed with organic coconut oil (OCO) during turning of hardened D2 steel. The application of cutting fluid on the cutting interface was performed through Minimum Quantity Lubrication (MQL) approach keeping an eye on the detrimental consequences of conventional flood cooling. PVD coated (TiN/TiCN/TiN) cermet tool was employed in the current experimental work. Taguchi’s L9 orthogonal array and TOPSIS are executed to analysis the influences, significance and optimum parameter settings for predefined process parameters. The prime objective of the current work is to analyze the influence of OCO based Trihexyltetradecylphosphonium Chloride ionic fluid on flank wear, surface roughness, material removal rate, and chip morphology. Better quality of finish (Ra = 0.2 to 1.82 µm) was found with 1% weight fraction but it is not sufficient to control the wear growth. Abrasion, chipping, groove wear, and catastrophic tool tip breakage are recognized as foremost tool failure mechanisms. The significance of responses have been studied with the help of probability plots, main effect plots, contour plots, and surface plots and the correlation between the input and output parameters have been analyzed using regression model. Feed rate and depth of cut are equally influenced (48.98%) the surface finish while cutting speed attributed the strongest influence (90.1%). The material removal rate is strongly prejudiced by cutting speed (69.39 %) followed by feed rate (28.94%) whereas chip reduction coefficient is strongly influenced through the depth of cut (63.4%) succeeded by feed (28.8%). TOPSIS significantly optimized the responses with 67.1 % gain in closeness coefficient.

Optimization of Cutting Parameters in Milling Process Using Genetic Algorithm and ANOVA (March 2020)

2020 ◽  
Vol 38 (10A) ◽  
pp. 1489-1503
Author(s):  
Marwa Q. Ibraheem
Keyword(s):  
Genetic Algorithm ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimal Value ◽  
Optimization Of Cutting Parameters

In this present work use a genetic algorithm for the selection of cutting conditions in milling operation such as cutting speed, feed and depth of cut to investigate the optimal value and the effects of it on the material removal rate and tool wear. The material selected for this work was Ti-6Al-4V Alloy using H13A carbide as a cutting tool. Two objective functions have been adopted gives minimum tool wear and maximum material removal rate that is simultaneously optimized. Finally, it does conclude from the results that the optimal value of cutting speed is (1992.601m/min), depth of cut is (1.55mm) and feed is (148.203mm/rev) for the present work.

Modeling of Material Removal Mechanism in Micro Electric Discharge Milling of Ti-6Al-4V

2014 ◽  
Vol 592-594 ◽  
pp. 516-520 ◽  
Author(s):  
Basil Kuriachen ◽  
Jose Mathew
Keyword(s):  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Milling Process ◽  
Work Piece ◽  
Machining Parameters ◽  
Removal Mechanism ◽  
Material Removal Mechanism ◽  
Electric Discharge Milling

Micro EDM milling process is accruing a lot of importance in micro fabrication of difficult to machine materials. Any complex shape can be generated with the help of the controlled cylindrical tool in the pre determined path. Due to the complex material removal mechanism on the tool and the work piece, a detailed parametric study is required. In this study, the influence of various process parameters on material removal mechanism is investigated. Experiments were planned as per Response Surface Methodology (RSM) – Box Behnken design and performed under different cutting conditions of gap voltage, capacitance, electrode rotation speed and feed rate. Analysis of variance (ANOVA) was employed to identify the level of importance of machining parameters on the material removal rate. Maximum material removal rate was obtained at Voltage (115V), Capacitance (0.4μF), Electrode rotational Speed (1000rpm), and Feed rate (18mm/min). In addition, a mathematical model is created to predict the material removal

Effect of WEDM process parameters on machinability of Nimonic75 alloy using brass wire

2020 ◽  
Vol 17 (3) ◽  
pp. 389-397
Author(s):  
Harvinder Singh ◽  
Vinod Kumar ◽  
Jatinder Kapoor
Keyword(s):  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Speed ◽  
Content Type ◽  
Response Characteristics ◽  
Nickel Based Alloy ◽  
Pulse On Time ◽  
Pulse Off Time

Purpose This study aims to investigate the influence of process parameters of wire electrical discharge machining (WEDM) of Nimonic75. Nimonic75 is a Nickel-based alloy mostly used in the aerospace industry for its strength at high temperature. Design/methodology/approach One factor at a time (OFAT) approach has been used to perform the experiments. Pulse on time, pulse off time, peak current and servo voltage were chosen as input process parameters. Cutting speed, material removal rate and surface roughness (Ra) were selected as output performance characteristics. Findings Through experimental work, the effect of process parameters on the response characteristics has been found. Results identified the most important parameters to maximize the cutting speed and material removal rate and minimize Ra. Originality/value Very limited research work has been done on WEDM of Nickel-based alloy Nimonic75. Therefore, the aim of this paper to conduct preliminary experimentation for identifying the parameters, which influence the response characteristics such as material removal rate, cutting speed, Ra, etc. during WEDM of Nickel-based alloy (Nimonic75) using OFAT approach and found the machinability of Nimonic75 for further exhaustive experimentation work.

Automatic Characterization of the Material Removal Rate in Laser Manufacturing of TiAl6V4 and Inconel 718

2009 ◽  
Author(s):  
Leonardo Orazi ◽  
Gabriele Cuccolini ◽  
Giovanni Tani
Keyword(s):  
Material Removal Rate ◽  
Inconel 718 ◽  
Material Removal ◽  
Numerical Models ◽  
Removal Rate ◽  
Industrial Applications ◽  
Milling Process ◽  
Laser Source ◽  
Automated Method ◽  
Laser Milling

In this paper a system for the automatic determination of the material removal rate during laser milling process is presented. “Laser milling” can be defined as an engraving process with a strictly controlled penetration depth. In industrial applications, when a new material have to be machined or a change in the system set-up occur the user has to perform a time-consuming experimental campaign in order to determine the correlation between the material removal rate and the process parameters. In these cases the numerical models present some limits due to the elevated calculation time requested to simulate the laser milling of industrial features. In the proposed system, based on a regression model approach, the empirical coefficients, that provide the material removal rate, are automatically generated by a specific software according to the different materials that have to be processed. A description of the automated method and the results obtained in engraving TiAl6V4 and Inconel 718 superalloy with a fiber laser are presented. The system can be adapted to every combination of material/laser source.

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