A particle swarm approach for multi-objective optimization of electrical discharge machining process

2014 ◽  
Vol 27 (6) ◽  
pp. 1171-1190 ◽  
Author(s):  
Chinmaya P. Mohanty ◽  
Siba Sankar Mahapatra ◽  
Manas Ranjan Singh
2020 ◽  
Vol 44 (2) ◽  
pp. 294-310
Author(s):  
Duc-Nguyen Van ◽  
Bong-Pham Van ◽  
Phan-Nguyen Huu

This study presents a hybrid Taguchi – analytic hierarchy process (AHP) – Deng’s similarity-based method for the multi-objective optimization of the electrical discharge machining process of SKD11. Among many parameters, the four most important parameters including current, voltage, pulse-on time, and pulse-off time are considered as control factors. The four quality characteristics including material removal rate, tool wear rate, surface roughness, hardness of machined surface, and white layer thickness were considered for simultaneous optimization. The hybrid Taguchi – AHP – Deng’s similarity-based multi-objective optimization was compared with several other methods to evaluate the effectiveness of this hybrid technique. The results show that the Taguchi – AHP – Deng’s similarity-based method is a good alternative to solve multi-objective optimization problems.


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