Theoretical and Experimental Estimation of Material Removal Rate of Electric-Spark Diamond Grinding of Difficult-To-Cut Materials

2022 ◽  
pp. 1317-1333
Author(s):  
Kumar Bhartendu ◽  
S. K. Jha ◽  
B. K. Bhuyan
Keyword(s):  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Diamond Grinding ◽  
Experimental Estimation

Intelligent Modeling and Optimization of Material Removal Rate in Electric Discharge Diamond Grinding

2012 ◽  
Author(s):  
Pankaj Kumar Shrivastava ◽  
Avanish Kumar Dubey
Keyword(s):  
Material Removal Rate ◽  
Electric Discharge ◽  
Material Removal ◽  
Removal Rate ◽  
Iron Carbide ◽  
Hybrid Approach ◽  
Weight Ratio ◽  
Manufacturing Industries ◽  
Machining Process ◽  
Diamond Grinding

Metal matrix composites (MMCs) have wide applications in modern manufacturing industries due to their specific and improved technological characteristics such as high strength to weight ratio, high hardness, high thermal, corrosion and wear resistances. Such characteristics are highly demanded in automobile, aircraft and space research organizations. Shaping of MMCs has been a big challenge for manufacturing industries due to their superior mechanical properties and the peculiar microstructure composed of different phases in MMCs poses machining challenges. Unconventional machining methods have become an alternative to give desired shapes with intricate profiles and stringent design requirements. The aim of present research is to investigate the machining performance of copper-iron-carbide MMC using hybrid machining process, electric discharge diamond grinding (EDDG). A hybrid approach of neural network and genetic algorithm has been used to develop the intelligent model for material removal rate (MRR) and subsequent optimization with the experimental data obtained by scientifically designed experimentation.

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.

Effect of SiC-Cu Electrode on Material Removal Rate, Tool Wear and Surface Roughness in EDM Process

2020 ◽  
Vol 38 (9A) ◽  
pp. 1406-1413
Author(s):  
Yousif Q. Laibia ◽  
Saad K. Shather
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
304 Stainless Steel ◽  
Tool Electrode ◽  
Pulse Time ◽  
Edm Process

Electrical discharge machining (EDM) is one of the most common non-traditional processes for the manufacture of high precision parts and complex shapes. The EDM process depends on the heat energy between the work material and the tool electrode. This study focused on the material removal rate (MRR), the surface roughness, and tool wear in a 304 stainless steel EDM. The composite electrode consisted of copper (Cu) and silicon carbide (SiC). The current effects imposed on the working material, as well as the pulses that change over time during the experiment. When the current used is (8, 5, 3, 2, 1.5) A, the pulse time used is (12, 25) μs and the size of the space used is (1) mm. Optimum surface roughness under a current of 1.5 A and the pulse time of 25 μs with a maximum MRR of 8 A and the pulse duration of 25 μs.

Enhancement of EDM Performance by Using Copper-Silver Composite Electrode

2020 ◽  
Vol 38 (9A) ◽  
pp. 1352-1358
Author(s):  
Saad K. Shather ◽  
Abbas A. Ibrahim ◽  
Zainab H. Mohsein ◽  
Omar H. Hassoon
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
High Speed ◽  
Composite Electrode ◽  
Removal Rate ◽  
Pure Copper ◽  
High Speed Steel ◽  
Pulse On Time ◽  
Pulse Off Time

Discharge Machining is a non-traditional machining technique and usually applied for hard metals and complex shapes that difficult to machining in the traditional cutting process. This process depends on different parameters that can affect the material removal rate and surface roughness. The electrode material is one of the important parameters in Electro –Discharge Machining (EDM). In this paper, the experimental work carried out by using a composite material electrode and the workpiece material from a high-speed steel plate. The cutting conditions: current (10 Amps, 12 Amps, 14 Amps), pulse on time (100 µs, 150 µs, 200 µs), pulse off time 25 µs, casting technique has been carried out to prepare the composite electrodes copper-sliver. The experimental results showed that Copper-Sliver (weight ratio70:30) gives better results than commonly electrode copper, Material Removal Rate (MRR) Copper-Sliver composite electrode reach to 0.225 gm/min higher than the pure Copper electrode. The lower value of the tool wear rate achieved with the composite electrode is 0.0001 gm/min. The surface roughness of the workpiece improved with a composite electrode compared with the pure electrode.

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.

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