Application of fuzzy technique for order preference by similarity to ideal solution in computer numerical control end milling of in-situ Al-4.5%Cu-TiC metal matrix composite. (September 2016)

• Record Type: Journal Article
• Authors: Das, Biswajit; Roy, Susmita; Rai, RN; Saha, SC
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 230:Number 9(2016:Sep.)
• Page Start: 1600
• Page End: 1613
• Publication Date: 2016-09
• Subjects: Metal matrix composites -- in-situ technique -- grey relational analysis -- fuzzy technique for order preference by similarity to ideal solution -- response surface analysis -- prediction model; Mechanical engineering -- Periodicals; Engineering -- Management -- Periodicals; Manufacturing processes -- Periodicals; 629.8
• DOI: 10.1177/0954405416666896
• Languages: English
• ISSNs: 0954-4054

Abstract

In the present investigation, an effort has been made to explore the outcome of cutting parameters (cutting speed, feed and depth of cut) on surface roughness parameters ( Ra, Rz ) and cutting force ( Fc ) using solid carbide end mill cutter. During the existing study, a novel fuzzy technique for order preference by similarity to ideal solution, grey relational and response surface analysis technique is utilized to find out the optimal settings of computer numerical control milling process parameters with an endeavour to improve the quality of the machined surface. Hence, generating optimum surface roughness values are essential to obtain high productivity in the manufacturing of different machined parts. In this article, the first motive is to investigate computer numerical control milling of Al-4.5%Cu-TiC metal matrix composite developed by in-situ technique using fuzzy technique for order preference by similarity to ideal solution and grey relational analysis to find out optimum cutting parameters. The second motive is to verify using response surface analysis mathematical model depending on cutting parameters of surface roughness and cutting force in milling. The potentiality of the developed model is proved by analysis of variance technique. The analysis of variance result shows that the depth of cut is the leading process parameter affecting the surface roughness and cutting force values.