Comparative evaluation of performances of TiAlN, AlCrN, TiAlN/AlCrN coated carbide cutting tools and uncoated carbide cutting tools on turning Inconel 825 alloy using Grey Relational Analysis

2018 ◽  
Vol 279 ◽  
pp. 331-342 ◽  
Author(s):  
Sampath Kumar T. ◽  
R. Ramanujam ◽  
M. Vignesh ◽  
N. Tamiloli ◽  
Nishant Sharma ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Comparative Evaluation ◽  
Cutting Tools ◽  
Relational Analysis ◽  
Grey Relational ◽  
Coated Carbide ◽  
Inconel 825

scholarly journals Multi-Response Optimization of cutting parameters in MQL assisted Turning of Haynes 25 alloy with Taguchi based Grey Relational Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Tushar Dhote ◽  
◽  
Rahul A Mali ◽  
Jitendra Katiyar ◽  
Gupta T V K ◽  
...  
Keyword(s):  
Grey Relational Analysis ◽  
Particle Concentration ◽  
Minimum Quantity Lubrication ◽  
Cutting Parameters ◽  
Nano Particle ◽  
Relational Analysis ◽  
Grey Relational ◽  
Optimization Of Cutting Parameters ◽  
Coated Carbide ◽  
Thrust Forces

Haynes 25 is a cobalt based superalloy gaining its importance in aerospace, heat treatment applications, chemical handling equipment, commercial gas turbine engines, bearing material, etc. This alloy is featured with low thermal conductivity, wear and corrosion resistance, strength with good resistance to oxidation at high temperatures. In the present study, optimization of process parameters in turning Haynes 25 alloy with uncoated and coated carbide tools under the minimum quantity lubrication (MQL) using Taguchi based grey relational analysis (GRA) method is attempted. The influence of cutting parameters and nano-particle concentration on surface roughness, tool wear, cutting and thrust forces are analyzed to improve the alloy machinability. The work also compares the responses obtained with uncoated and coated tool inserts and analyzes the effect of nano-particle concentration. Further, the experimental cutting and thrust forces are computed and validated using FE based DEFORM 3D software. The results obtained through simulation are in good accordance with experimental data within an average relative error of about 12 %.

Optimization of Reaming Process Parameters for Alloy Grey Cast Iron HT250 Using Grey Relational Analysis

2020 ◽  
Vol 866 ◽  
pp. 32-41
Author(s):  
C. Ye ◽  
X.R. Shi ◽  
L. Chen ◽  
Yong Guo Wang
Keyword(s):  
Tool Wear ◽  
Grey Relational Analysis ◽  
Feed Rate ◽  
Optimization Technique ◽  
Cutting Speed ◽  
Hole Quality ◽  
Crater Wear ◽  
Relational Analysis ◽  
Grey Relational ◽  
Coated Carbide

Reaming is one of the finishing processes that has been widely applied in automotive industry. Reaming parameters were evaluated and optimized based on multiple performance characteristics including tool wear and hole quality. Taguchi’s L16, 4-level, 2-factor orthogonal array (OA) was conducted for this test. It was shown that crater wear and flank wear were seen on the tool surface. Furthermore, the crater wear was also of major significance. Hole quality was discovered to be mostly dependent upon cutting speed and feed rate. TiAlN coated carbide reamer shows the best performance with respect to the tool wear as well as hole quality. Grey relational analysis used as a multiple-response optimization technique found that feed rate was the more influential parameter than cutting speed. The goal of the experimental results was to obtain both minimum diametral error and the value of surface roughness by adopting the optimal combination of the reaming parameters.

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