Modelling and optimisation of cutting parameters on surface roughness in micro-milling Inconel 718 using response surface methodology and genetic algorithm

2018 ◽  
Vol 14 (1) ◽  
pp. 34 ◽  
Author(s):  
Xiaohong Lu ◽  
Furui Wang ◽  
Xinxin Wang ◽  
Likun Si
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Inconel 718 ◽  
Cutting Parameters ◽  
Micro Milling

Investigation of Machining Parameters in CNC Turning of EN3 Low Carbon Steel Using Genetic Algorithm and Response Surface Methodology

2014 ◽  
Vol 592-594 ◽  
pp. 883-887
Author(s):  
R. Rave Kumar ◽  
M. Mohamed Abdul Hafeez ◽  
K. Velmanirajan ◽  
K. Nantha Kumar
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Response Surface Methodology ◽  
Carbon Steel ◽  
Response Surface ◽  
Low Carbon Steel ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Low Carbon

Burrs are bottleneck of precision machining and automation production. Burrs are formed in every edges and faces, during the turning process, which affects the quality level of surface roughness. In this paper the experimental study of EN3 low carbon steel were carried out to minimize the surface roughness using response surface methodology and genetic algorithm. Tungsten Carbide was used as a cutting tool for this turning operation. Machined samples are examined under Scanning Electron Microscope (SEM) for burr formation. A wide variety of analysis between cutting parameters have been shown graphically. The minimization of burr was achieved and hence better surface quality was obtained by optimizing the cutting parameters like cutting speed, feed, and depth of cut, with the aid of Genetic Algorithm (GA) & Response Surface Methodology (RSM) Techniques.

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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