scholarly journals Multi-Response Optimization of WEDM Process Parameters Using Taguchi Based Desirability Function Analysis

2018 ◽  
Vol 338 ◽  
pp. 012004 ◽  
Author(s):  
Himadri Majumder ◽  
Kalipada Maity
Keyword(s):  
Process Parameters ◽  
Function Analysis ◽  
Desirability Function ◽  
Response Optimization ◽  
Desirability Function Analysis ◽  
Wedm Process

Multi-Response Optimization in Turning of AA6061 T6 Using Desirability Function Analysis

2015 ◽  
Vol 812 ◽  
pp. 124-129 ◽  
Author(s):  
P. Jayaraman ◽  
L. Mahesh Kumar
Keyword(s):  
Function Analysis ◽  
Removal Rate ◽  
Desirability Function ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Multiple Responses ◽  
Ideal Approach ◽  
Response Optimization ◽  
Desirability Function Analysis

This paper presents an ideal approach for the optimization of machining parameters on turning of AA6061 T6 aluminium alloy with multiple responses based on orthogonal array with desirability function analysis. In this study, turning parameters namely cutting speed, feed rate and depth of cut are optimized with the considerations of multiple responses such as surface roughness (Ra), roundness (Ø) and material removal rate (MRR). Multi response optimization of machining parameters was done through desirability function analysis. The optimum machining parameters have been identified by a composite desirability value obtained from desirability function analysis. The performance index and significant contribution of process parameters were determined by analysis of variance.

Multiple Performance Optimization in WEDM Parameters Using Desirability Analysis

2015 ◽  
Vol 813-814 ◽  
pp. 352-356 ◽  
Author(s):  
S. Vijaya Bhaskar ◽  
T. Rajmohan ◽  
G.R. Giri Sesha Sai ◽  
G. Sandeep Kumar Reddy
Keyword(s):  
Surface Roughness ◽  
Analysis Of Variance ◽  
Process Parameters ◽  
Performance Optimization ◽  
Function Analysis ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Desirability Function Analysis ◽  
Wedm Process

In this article, the effect of wire electrical discharge machining (WEDM) parameters such as pulse-on time (TON), pulse-off time (TOFF), and wire feed (F) on material removal rate (MRR) and surface roughness in metal matrix composites (MMCs) consisting of aluminium alloy (A1356) silicon carbide (SiCp) and Mica is discussed. The Al 356 is reinforced with SiCp and Mica in the form of particulates. The experiments are carried out as per design of experiments approach using L9 orthogonal array. The optimum machining parameters have been identified by a composite desirability value obtained from desirability function analysis as the performance index, and significant contribution of parameters can then be determined by analysis of variance (ANOVA). Confirmation test is also conducted to validate the test result. Experimental results have shown that machining performance can be improved effectively through this approach. The results were analysed using analysis of variance and response graphs. It is found that different combinations of WEDM process parameters are required to achieve higher MRR and minimum surface roughness for composites. These results will be useful for manufacturing engineers to select appropriate WEDM process parameters to machine MMCs of Al 356 reinforced with SiC and Mica.

Multi-Response Optimization of Micro-WEDM Process Parameters of Ti49.4-Ni50.6 Shape Memory Alloy for Orthopedic Implant Application

2018 ◽  
Vol 1150 ◽  
pp. 1-21
Author(s):  
Adik M. Takale ◽  
Nagesh K. Chougule ◽  
Preetam H. Selmokar ◽  
M.G. Gawari
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Process Parameters ◽  
Removal Rate ◽  
Orthopedic Implant ◽  
Wire Tension ◽  
Response Optimization ◽  
Micro Wedm ◽  
Wedm Process ◽  
Wire Feed

The present work deals with the optimization of micro-WEDM process parameters for machining Ti49.4-Ni50.6 shape memory alloy (SMA) for orthopedic implant application. Effect of micro-WEDM parameters viz. Gap voltage, capacitance, wire feed and wire tension on the response variables such as material removal rate, surface roughness, kerf width and dimensional deviation is determined. As Ti-Ni SMA has fascinating properties and bio-compatibility, have been considered for present work. Nine experiments have been performed on micro-WEDM based on an orthogonal array of Taguchi method. Subsequently, the grey relational analysis (GRA) method is applied to determine an optimal set of process parameters. It is observed that optimized set of parameters A3B3C3D1 viz. 140 V gap voltage, 0.4 µF capacitance, wire feed 30 µm/sec and 30% of wire tension determined by using GRA offers maximum MRR and minimum SR, KW and DD. From the Analysis of Variance, it is seen that the process parameter capacitance is the most significant parameter for multi-response optimization with a percentage contribution of 77.91%. Young’s modulus also checked for biocompatibility. Also, SEM images are taken to confirm the results offering better surface quality. Heat treatment process like annealing is found to be the most suitable to recover shape memory effect of WEDMed samples.

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