Optimization of Nickel Alloy Turning Considering the Tool in Different Wear Phases

2017 ◽  
Vol 261 ◽  
pp. 243-250
Author(s):  
Wojciech Zębala
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Material Removal ◽  
Tool Path ◽  
Removal Rate ◽  
Aircraft Engine ◽  
Material Model ◽  
Turning Process ◽  
Engine Part ◽  
Nickel Based Alloy

Paper presents some turning process optimization investigations, concerning modeling of tool wear when turning a difficult-to-cut material like nickel based alloy. The workpiece was an aircraft engine part in the form of disc. The aim of the research was an optimization of the cutting data (feed rate) for the purpose to improve the cutting process (stabilization of the cutting force course along the tool path) and increase the material removal rate (efficiency of the machining). A “force material model”, based on the tool behavior in its different wear phases was established.

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.

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.

Process Design and Optimization of end Milling Parameters of Al 7075 Metal Matrix Composite

2021 ◽  
pp. 929-937
Author(s):  
D. S. Sai Ravi Kiran ◽  
Alavilli Sai Apparao ◽  
Vempala GowriSankar ◽  
Shaik Faheem ◽  
Sheik Abdul Mateen ◽  
...  
Keyword(s):  
Tool Wear ◽  
Material Removal Rate ◽  
Metal Matrix ◽  
Material Removal ◽  
Hybrid Composites ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Weight Percentage

This paper investigates the machinability characteristics of end milling operation to yield minimum tool wear with the maximum material removal rate using RSM. Twenty-seven experimental runs based on Box-Behnken Design of Response Surface Methodology (RSM) were performed by varying the parameters of spindle speed, feed and depth of cut in different weight percentage of reinforcements such as Silicon Carbide (SiC-5%, 10%,15%) and Alumina (Al2O3-5%) in alluminium 7075 metal matrix. Grey relational analysis was used to solve the multi-response optimization problem by changing the weightages for different responses as per the process requirements of quality or productivity. Optimal parameter settings obtained were verified through confirmatory experiments. Analysis of variance was performed to obtain the contribution of each parameter on the machinability characteristics. The result shows that spindle speed and weight percentage of SiC are the most significant factors which affect the machinability characteristics of hybrid composites. An appropriate selection of the input parameters such as spindle speed of 1000 rpm, feed of 0.02 mm/rev, depth of cut of 1 mm and 5% of SiC produce best tool wear outcome and a spindle speed of 1838 rpm, feed of 0.04 mm/rev, depth of cut of 1.81 mm and 6.81 % of SiC for material removal rate.

CHARACTERIZATION OF ZrB2-SiC COMPOSITES WITH AN ANALYTICAL STUDY ON MATERIAL REMOVAL RATE AND TOOL WEAR RATE DURING ELECTRICAL DISCHARGE MACHINING

2016 ◽  
Vol 40 (3) ◽  
pp. 331-349 ◽  
Author(s):  
S. Sivasankar ◽  
R. Jeyapaul
Keyword(s):  
Wear Rate ◽  
Tool Wear ◽  
Relative Density ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Tool Wear Rate ◽  
Tool Materials

This research work concentrates on Electrical Discharge Machining (EDM) performance evaluation of ZrB2- SiC ceramic matrix composites with different tool materials at various machining parameters. Monolithic ZrB2 possesses lower relative density (98.72%) than composites. ZrB2 with 20 Vol.% of SiC possesses 99.74% of the relative density with improved hardness values. Bend strength and Young’s modulus increase with SiC addition until it reaches 20 Vol% and then decreasing. EDM performance on tool materials of tungsten, niobium, tantalum, graphite and titanium at various levels of pulse on time and pulse off time are analyzed. Graphite produces the best Material removal rate (MRR) for all the workpieces. Tool wear rate decreases with melting point and thermal conductivity of the tool material.

scholarly journals Investigation an assisting electrode powder mixed electrical discharge machining of nonconductive ceramic

2021 ◽  
Author(s):  
Dragan Rodic ◽  
Marin Gostimirovic ◽  
Milenko Sekulic ◽  
Borislav Savkovic ◽  
Branko Strbac
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Metal Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Positive Effects ◽  
Assisting Electrode

Abstract It is well known that electrical discharge machining can be used in the processing of nonconductive materials. In order to improve the efficiency of machining modern engineering materials, existing electrical discharge machines are constantly being researched and improved or developed. The current machining of non-conductive materials is limited due to the relatively low material removal rate and high surface roughness. A possible technological improvement of electrical discharge machining can be achieved by innovations of existing processes. In this paper, a new approach for machining zirconium oxide is presented. It combines electrical discharge machining with assisting electrode and powder-mixed dielectric. The assisting electrode is used to enable electrical discharge machining of nonconductive material, while the powder-mixed dielectric is used to increase the material removal rate, reduce surface roughness, and decrease relative tool wear. The response surface method was used to generate classical mathematical models, analyzing the output performances of surface roughness, material removal rate and relative tool wear. Verification of the obtained models was performed based on a set of new experimental data. By combining these latest techniques, positive effects on machining performances are obtained. It was found that the surface roughness was reduced by 18%, the metal removal rate was increased by about 12% and the relative tool wear was reduced by up to 6% compared to electrical discharge machining with supported electrode without powder.

Fabrication and experimental investigation of magnetic field assisted powder mixed electrical discharge machining on machining of aluminum 6061 alloy

2019 ◽  
Vol 233 (12) ◽  
pp. 2283-2291 ◽  
Author(s):  
Arun Kumar Rouniyar ◽  
Pragya Shandilya
Keyword(s):  
Magnetic Field ◽  
Wear Rate ◽  
Tool Wear ◽  
Material Removal Rate ◽  
Electrical Discharge ◽  
Material Removal ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Tool Wear Rate ◽  
Pulse On Time

Magnetic field assisted powder mixed electrical discharge machining is a hybrid machining process with suitable modification in electrical discharge machining combining the use of magnetic field and fine powder in the dielectric fluid. Aluminum 6061 alloy has found highly significance for the advanced industries like automotive, aerospace, electrical, marine, food processing and chemical due to good corrosion resistance, high strength-to-weight ratio, ease of weldability. In this present work, magnetic field assisted powder mixed electrical discharge machining setup was fabricated and experiments were performed using one factor at a time approach for aluminum 6061 alloy. The individual effect of machining parameters namely, peak current, pulse on time, pulse off time, powder concentration and magnetic field on material removal rate and tool wear rate was investigated. The effect of peak current was found to be dominant on material removal rate and tool wear rate followed by pulse on time, powder concentration and magnetic field. Increase in material removal rate and tool wear rate was observed with increase in peak current, pulse on time and a decrease in pulse off time, whereas, for material removal rate increases and tool wear rate decreases up to the certain value and follow the reverse trend with an increase in powder concentration. Material removal rate was increased and tool wear rate was decreased with increase in magnetic field.

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