Reconnoitering the influence of Nano fluid of Nano boracic acid particles enriched waste coconut oil in Machining SAE 1045 shaft on modification Surface finish. (2022)

• Record Type: Journal Article
• Authors: Saravanan, R.; Rajesh, S.; Gnanavel, C.; Malladi, Avinash; Sekar, C.B.; Nagarathi, D.K.
• Is Part Of: Materials today. Volume 62:Part 2(2022)
• Page Start: 1330
• Page End: 1335
• Publication Date: 2022
• Subjects: Surface Roughness -- Waste -- Novel Nano fluid -- Boric acid -- Sample size, SAE 1045; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.04.745
• Languages: English
• ISSNs: 2214-7853

Abstract

Highlights: Nanofluid prepared from the used coconut oil that is waste coconut oil. Novel application of Nanofluid in flood cooling is investigated. Machined surface quality improved by reduction of average surface roughness from 12.3237 µm to 8.2844 µm. The optimized process parameters by Taguchi analysis 190 m/min cutting velocity and 0.20 tool feed rate and 0.3 mm nose radius. Taguchi Experimental design and Analysis employed in this investigation. Abstract: The surface quality is a prime factor in the failures of shaft by fatigue load. Here used coconut oil or waste coconut oil from Kerala chips shop are used for lubricating purpose for machining the precision shaft. This piece of research work investigating the effect of Nano fluid of Nano boric acid nanoparticles concentrated 'used waste coconut oil' for machining steel in the semiautomated lathe. The motor shafts are machined in dry condition called green machining then used polishing to reduces the surface roughness. This research tried to reduces the cost of manufacturing by using a low cost Nanofluid as coolant and lubricant in the cutting zone. Used coconuts oils are disposed as waste in many sweet and snacks shops. From such waste machine coolant is developed. The same was tested at conventional machining requirements and compared. Taguchi L16 orthogonal array employed as this investigation considered its 3 process variables at 4 levels. The process parameters analyzed and optimized by Taguchi analysis. The results recommended the proposed method as it outperformed.