Optimization on WEDM for Maximum Material Removal Rate When Cutting Half Round of SKD11 Steel

2022 ◽  
pp. 767-774
Author(s):  
Trinh Kieu Tuan ◽  
Hoang Xuan Tu ◽  
Dang Quoc Cuong ◽  
Le Hoang Anh ◽  
Nguyen Anh Tuan ◽  
...  
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Maximum Material Removal Rate

Optimization of Cutting Parameters in Machining GFRP Using End Mill Cutter through DoE and Verification through Genetic Algorithm

2017 ◽  
Vol 867 ◽  
pp. 134-147
Author(s):  
Shanmugasundaram Sankar ◽  
V. Kumaresan Manivarma
Keyword(s):  
Genetic Algorithm ◽  
Material Removal Rate ◽  
Surface Finish ◽  
Material Removal ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Machining Parameters ◽  
End Mill ◽  
Mill Cutter ◽  
Maximum Material Removal Rate

This article discusses optimization of critical parameters such as cutting speed, feed, depth of cut and method of machining while machining Glass Fiber Reinforced Plastic (GFRP) in vertical machining center using standard end mill cutter made up of High Speed Steel (HSS) for lesser cutting load, maximum material removal rate for better surface finish and dimensional accuracy through design of experiments. In composite material machining, surface finish is the critical deciding factor in determining surface quality. In this study, as per Taguchi’s L9 orthogonal array, predictable and unpredictable parts are followed to evaluate the consequence of cutting parameters on the machined component. The study includes surface roughness measurement using surface profilometer continued by physical measurement of machined pocket dimension. The experimental results, suggest suitable machining parameters in order to achieve the above target goal. In addition, C++ program is developed to cross check the most favorable machining parameters for maximum material removal rate using genetic algorithm. It is inferred from the study that the genetic algorithm results coincides very closely with the result given by the method of design of experiments.

An Experimental Study on Grinding Fir-Tree Root Forms Using Vitrified CBN Wheels

2014 ◽  
Vol 1017 ◽  
pp. 55-60 ◽  
Author(s):  
Zhong De Shi ◽  
Amr Elfizy ◽  
Helmi Attia
Keyword(s):  
Experimental Study ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Turbine Blades ◽  
Wheel Wear ◽  
Part Quality ◽  
Grinding Conditions ◽  
Vitrified Cbn ◽  
Maximum Material Removal Rate

An experimental study was undertaken to explore the conditions and performance on rough and finish grinding fir-tree root forms of turbine blades made of a nickel-based alloy using vitrified CBN wheels and water-based grinding fluid. This work was motivated by switching the grinding of fir-tree root forms from grinding with conventional abrasive wheels to vitrified CBN wheels for reducing overall production cost and enhancing productivity. Grinding experiments were conducted to measure grinding forces, power, surface roughness, and stress near the blade roots under various dressing and grinding conditions. Wheel re-dressing life in terms of the total number of good parts ground between dressing was tested with the condition producing the maximum material removal rate while satisfying preset part quality and process requirements. It was found that the maximum material removal rate achievable in rough grinding was restricted by the stress limit and the wheel re-dressing life was dominated by the radial wheel wear limit. The targeting part quality and process requirements were achieved. It was proved that vitrified CBN grinding process is feasible and very promising to machine fir-tree root forms.

scholarly journals Multi-objective parametric optimization for high surface quality and process efficiency in micro-grinding

2020 ◽  
pp. 002029402094495
Author(s):  
Jun Wang ◽  
Qiang Ye ◽  
Man Zhao ◽  
Xusheng Shi ◽  
Tingwei Fei
Keyword(s):  
Genetic Algorithm ◽  
Response Surface Methodology ◽  
Particle Swarm Optimization ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Desirability Function ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Maximum Material Removal Rate

In this study, for the selection of maximum material removal rate and minimum surface roughness [Formula: see text] in micro-grinding of aluminum alloy through multi-response optimization, two optimization approaches are proposed based on statistical analysis and genetic algorithm. The statistical analysis–based approach applies response surface methodology according to the analysis of variance to propose a mathematical model for [Formula: see text]. In addition, the individual desirability of material removal rate, [Formula: see text], and the global desirability function are calculated, and the inverse analysis is conducted to locate input setting giving maximum desirability function. The genetic algorithm–based approach uses the improved multi-objective particle swarm optimization with the experimental data trained by support vector machine. To demonstrate that the material microstructure is a significant parameter for material removal rate and [Formula: see text], the models with and without Taylor factor consideration are developed and compared. The optimized results achieved from both response surface methodology and improved multi-objective particle swarm optimization demonstrate that the consideration of Taylor factor can significantly improve the optimization process to achieve the maximum material removal rate and minimum [Formula: see text].

The Mechanism of Polymer Particles in Silicon Wafer CMP

2009 ◽  
Vol 626-627 ◽  
pp. 231-236 ◽  
Author(s):  
Xue Feng Xu ◽  
H.F. Chen ◽  
H.T. Ma ◽  
B.X. Ma ◽  
Wei Peng
Keyword(s):  
Silicon Wafer ◽  
Material Removal Rate ◽  
Material Removal ◽  
Colloidal Silica ◽  
Removal Rate ◽  
Polymer Particle ◽  
Silica Shell ◽  
Polymer Particles ◽  
Interaction Potential Energy ◽  
Maximum Material Removal Rate

In order to increase the material removal rate of silicon wafer, composite abrasives slurry was used in CMP. Zeta potential of polymer particle was measured and interaction potential energy between silica abrasives and polymer particles in slurry were analyzed and calculated. Adsorptions between silica abrasives and polymer particles were observed with TEM. CMP experiments had been taken to analyze the effects of polishing parameters (the concentration of colloidal silica and polymer particle, the pressure and the speed of polishing) on the material removal rate. The mechanism of polymer particle in polishing was elaborated. Experimental results indicated that PS, PMMA and BGF polymer particles could adsorb silica abrasives in slurry. Silica shell/PS core, silica shell/PMMA core and silica shell/BGF core particles could be used to formulate composite abrasives slurries. The material removal rate with composite abrasives slurry was higher than that of single abrasive slurry. The maximum material removal rate was obtained with silica shell/BGF core composite abrasives slurry.

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.

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