Development of Non-dominated Genetic Algorithm Interface for Parameter Optimization of Selected Electrochemical-Based Machining Processes

Author(s):  
D. Singh ◽  
R. S. Shukla
2014 ◽  
Vol 56 (9) ◽  
pp. 728-736 ◽  
Author(s):  
Krishnasamy Vijaykumar ◽  
Kavan Panneerselvam ◽  
Abdullah Naveen Sait

2016 ◽  
Vol 90 ◽  
pp. 559-565 ◽  
Author(s):  
G. Arunkumar ◽  
I. Gnanambal ◽  
S. Naresh ◽  
P.C. Karthik ◽  
Jagadish Kumar Patra

Author(s):  
Deepak Rajendra Unune ◽  
Amit Aherwar

Inconel 718 superalloy finds wide range of applications in various industries due to its superior mechanical properties including high strength, high hardness, resistance to corrosion, etc. Though poor machinability especially in micro-domain by conventional machining processes makes it one of the “difficult-to-cut” material. The micro-electrical discharge machining (µ-EDM) is appropriate process for machining any conductive material, although selection of machining parameters for higher machining rate and accuracy is difficult task. The present study attempts to optimize parameters in micro-electrical discharge drilling (µ-EDD) of Inconel 718. The material removal rate, electrode wear ratio, overcut, and taper angle have been selected as performance measures while gap voltage, capacitance, electrode rotational speed, and feed rate have been selected as process parameters. The optimum setting of process parameters has been obtained using Genetic Algorithm based multi-objective optimization and verified experimentally.


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