Predictive model development and optimization of surface roughness parameter in milling operations by means of fuzzy logic and artificial neural network approach. (November 2019)

• Record Type: Journal Article
• Authors: Vignesh, M; Sasindran, Visnu; Arvind Krishna, S; Madusudhanan, A; Gokulachandran, J
• Is Part Of: IOP conference series. Volume 577(2019)
• Publication Date: 2019-11
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/577/1/012011
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: The advancement of artificial intelligence in the field of manufacturing has led to innovative methods to enhance productivity. Introduction of soft computing and machine learning techniques in industries have played a major role in reducing costs and increasing process efficiency. Optimization of machining processes such as surface finish brings about significant reduction in manufacturing costs. This research paper develops an optimization model by comparing two approaches – fuzzy logic and artificial neural network (ANN). The experiment is designed using Taguchi approach and the model is developed using fuzzy logic and ANN techniques. The validation is done for both the techniques and the one that provides minimal error is selected for predictive and optimization analysis. The selected method is suggested to be used in industries to optimize surface finish.