CNC Turning Process Parameters Optimization for Stainless Steel

2021 ◽  
pp. 59-64
Author(s):  
Surendra Kumar Saini ◽  
Prashant Kumar
Keyword(s):  
Stainless Steel ◽  
Process Parameters ◽  
Parameters Optimization ◽  
Turning Process ◽  
Process Parameters Optimization ◽  
Cnc Turning ◽  
Cnc Turning Process

CNC turning process parameters optimization on Aluminium 6082 alloy by using Taguchi and ANOVA

2020 ◽  
Vol 21 ◽  
pp. 1013-1021 ◽  
Author(s):  
S.P. Palaniappan ◽  
K. Muthukumar ◽  
R.V. Sabariraj ◽  
S. Dinesh Kumar ◽  
T. Sathish
Keyword(s):  
Process Parameters ◽  
Parameters Optimization ◽  
Turning Process ◽  
Process Parameters Optimization ◽  
Cnc Turning ◽  
Cnc Turning Process

Multi-response optimization of CNC turning parameters of austenitic stainless steel 303 using Taguchi-based grey relational analysis

2020 ◽  
Vol 44 (4) ◽  
pp. 592-601
Author(s):  
S.R. Sundara Bharathi ◽  
D. Ravindran ◽  
A. Arul Marcel Moshi
Keyword(s):  
Stainless Steel ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Regression Equations ◽  
Turning Process ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational ◽  
Cnc Turning Process

Extensive research has been carried out to optimize the process parameters of several machining processes. Optimizing the influencing parameters of the turning operation is a precise action that determines the desired level of quality. This study focuses on the multi-criteria optimization of the CNC turning process parameters of stainless steel 303 (SS 303) material to achieve minimum surface roughness (Ra) with maximum material removal rate (MRR) by means of Taguchi-based grey relational analysis. A CNC machine was tested following Taguchi’s L9 orthogonal array design. Grey relational analysis was used as the multi-criteria optimization tool. The significance of each individual process parameter on the overall characteristics of the turned specimen was estimated using analysis of variance (ANOVA). Regression equations were generated using the input factors with the selected output parameters. In addition, a morphological study of the chips produced by the turning process was carried out using SEM images in order to relate the chip geometry with the output responses.

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