Response Surface Methodology and Artificial Neural Network-Based Models for Predicting Performance of Wire Electrical Discharge Machining of Inconel 718 Alloy

Response Surface Methodology and Artificial Neural Network-Based Models for Predicting Performance of Wire Electrical Discharge Machining of Inconel 718 Alloy

This paper deals with the development and comparison of prediction models established using response surface methodology (RSM) and artificial neural network (ANN) for a wire electrical discharge machining (WEDM) process. The WEDM experiments were designed using central composite design (CCD) for mac...

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Bibliographic Details
Main Authors: Vishal Lalwani, Priyaranjan Sharma, Catalin Iulian Pruncu, Deepak Rajendra Unune
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Journal of Manufacturing and Materials Processing
Subjects:
response surface method (RSM)
artificial neural network (ANN)
wire electrical discharge machining (WEDM)
kerf width (Kf)
surface roughness (Ra)
material removal rate (MRR), NSGA-II
Online Access:https://www.mdpi.com/2504-4494/4/2/44

Internet

https://www.mdpi.com/2504-4494/4/2/44

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