Optimization of process parameters for rectangular cup deep drawing by the Taguchi method and genetic algorithm

2016 ◽  
Vol 58 (3) ◽  
pp. 238-245 ◽  
Author(s):  
Bora Sener ◽  
Hasan Kurtaran
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Process Parameters ◽  
Deep Drawing ◽  
Optimization Of Process Parameters

scholarly journals Optimization of process parameters in machining of nimonic super-alloy on EDM using genetic algorithm

2020 ◽  
Vol 2 (1) ◽  
pp. 35-44
Author(s):  
Madderla Sandhya ◽  
D. Ramasamy ◽  
Irshad ahamad Khilji ◽  
Anil Kumar ◽  
S. Chandramouli ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Process Parameters ◽  
Significant Influence ◽  
Optimal Choice ◽  
Copper Electrode ◽  
Taguchi Design Of Experiments ◽  
Optimization Of Process Parameters ◽  
Pulse On Time ◽  
Machining Characteristics

This project aims to investigate and predict the optimal choice for each EDM parameter using Taguchi Method by conducting a limited number of experiments on “Nimonic” Material. These parameters have a significant influence on the machining characteristics like MRR and TWR. Taguchi design of experiments (DOE) are implemented, particularly L9 orthogonal array is chosen and the effect of dominating process parameters is evaluated using analysis of variance. Nimonic refers to a family of Nickel-based high-temperature low creep superalloys. Due to its ability to withstand very high temperatures, Nimonic is ideal for typical applications such as aircraft parts, gas turbine components and blades, exhaust nozzles etc., for instance, where the pressure and heat are extreme. However, the conventional methods are not suitable to machine the hardest material such as Nimonic superalloy. The EDM, one of the popular unconventional machining methods, is used to the machine with a copper electrode, which in turn uses Taguchi methodology to analyze the effect of each parameter on the machining characteristics. The optimal choice for each EDM parameter such as peak current, gap voltage, duty cycle and pulse on time using the Taguchi method and Genetic Algorithm are identified. These parameters have a significant influence on machining characteristics such as MRR, EWR and surface roughness.

Optimization of Process Parameters in Plasma Arc Cutting Applying Genetic Algorithm and Fuzzy Logic

2018 ◽  
pp. 123-139
Author(s):  
Nehal Dash ◽  
Apurba Kumar Roy ◽  
Sanghamitra Debta ◽  
Kaushik Kumar
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Fuzzy Logic ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Optimization Of Process Parameters

Plasma Arc Cutting (PAC) process is a widely used machining process in several fabrication, construction and repair work applications. Considering gas pressure, arc current and torch height as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness would be considered as factors that determines the quality, machining time and machining cost. In order to reduce the number of experiments Design of Experiments (DOE) would be carried out. In later stages applications of Genetic Algorithm (GA) and Fuzzy Logic would be used for Optimization of process parameters in Plasma Arc Cutting (PAC). The output obtained would be minimized and maximized for Surface Roughness and Material Removal Rate respectively using Genetic Algorithm (GA) and Fuzzy Logic.

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