scholarly journals Optimization of Cutting Parameters for Cutting Force Minimization in Helical Ball End Milling of Inconel 718 by Using Genetic Algorithm

Procedia CIRP ◽  
2018 ◽  
Vol 77 ◽  
pp. 477-480 ◽  
Author(s):  
Varsharani Gaikhe ◽  
Jambeswar Sahu ◽  
Raju Pawade
Keyword(s):  
Genetic Algorithm ◽  
Cutting Force ◽  
Inconel 718 ◽  
End Milling ◽  
Cutting Parameters ◽  
Ball End Milling ◽  
Optimization Of Cutting Parameters

Optimization of Cutting Parameters for End Milling AlSi/AlN Metal Matrix Composite Using the Taguchi Method

2013 ◽  
Vol 773-774 ◽  
pp. 429-436 ◽  
Author(s):  
Siti Haryani Tomadi ◽  
Jaharah A. Ghani ◽  
Che Hassan Che Haron ◽  
Abdul Razak Daud
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Matrix Composite ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Cutting Conditions ◽  
Optimum Cutting ◽  
Optimization Of Cutting Parameters

In this paper, the optimization of cutting parameters is investigated to assess surface roughness and cutting force in the end milling of AlSi/AlN metal matrix composite. Eighteen experiments (L18) with five factors (cutting speed, feed rate, depth of cut, volume of particle reinforcement, and type of coated insert) were performed based on Taguchi designs of the experiment method. Two types of coating (TiB2 and TiN/TiCN/TiN) of the carbide cutting tool were employed to machine various volumes of AlN particle (5%, 7% and 10%) reinforced AlSi alloy matrix composite under dry cutting conditions. Signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were applied to investigate the optimum cutting parameters and their significance. The S/N analysis of the obtained results showed that the optimum cutting conditions for the cutting force were; A2 (triple coating of the insert), B2 (cutting speed: 200m/min), C1 (feed rate: 0.6mm/tooth), D1 (axial depth: 0.6mm) and E1 (5% reinforcement). At the mean time, the optimum cutting conditions for surface roughness were; A1 (single coating of insert), B3 (cutting speed: 250m/min), C2 (feed rate: 0.75mm/tooth), D1 (axial depth: 0.6mm) and E1 (5% reinforcement).The study confirmed that, with a minimum number of experiments, the Taguchi method is capable of determining the optimum cutting conditions for the cutting force and surface roughness for this new material under investigation.

Investigation of Dry Cutting and Applications of Cutting Fluid in Ball-End Milling Process

2011 ◽  
Vol 291-294 ◽  
pp. 3013-3023 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Channarong Rungruang
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
End Milling ◽  
Cutting Parameters ◽  
Milling Process ◽  
Cutting Fluid ◽  
Cutting Condition ◽  
Dry Cutting ◽  
Ball End Milling ◽  
End Milling Process

In order to realize the environmental hazard, this paper presents the investigation of the machinability of ball-end milling process with the dry cutting, the wet cutting, and the mist cutting for aluminum. The relations of the surface roughness, the cutting force, and the cutting parameters are examined based on the experimental results by using the Response Surface Analysis with the Box-Behnken design. The in-process cutting force is monitored to analyze the relations of the surface roughness and the cutting parameters. The proper cutting condition can be determined easily referring to the minimum use of cutting fluid, and the minimum surface roughness and cutting force of the surface plot. The effectiveness of the obtained surface roughness and cutting force models have been proved by utilizing the analysis of variance at 95% confident level.

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.

Parameter Optimization of Ball End Milling Process on Inconel 718 Using RSM and TLBO Algorithm

2015 ◽  
Vol 15 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Integrity ◽  
Inconel 718 ◽  
Tool Path ◽  
End Milling ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Ball End Milling

AbstractThis paper presents the application of Response Surface Methodology (RSM) coupled with Teaching Learning Based Optimization Technique (TLBO) for optimizing surface integrity of thin cantilever type Inconel 718 workpiece in ball end milling. The machining and tool related parameters like spindle speed, milling feed, axial depth of cut and tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate. Mathematical relationship between process parameters and deflection, surface roughness and microhardness are found out by using response surface methodology. It is observed that after optimizing the process that at the spindle speed of 2,000 rpm, feed 0.05 mm/tooth/rev, plate thickness of 5.5 mm and 15° workpiece inclination with horizontal tool path gives favorable surface integrity.

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