• ARSHID AHMAD SHAH
• Er. Deepak
• Mr. Sachin Syan

This work mainly focuses on the experimental optimization of cutting parameters primarily based on Surface roughness and material removal rate (MRR) and in this Experiment Central Composite Design is used to enhance surface roughness quality .Exclusive cutting parameters such as Cutting speed, Feed, and depth of cut,were examined by using covered Carbide equipment on CNC machines using EN24 (dry and wet machining) data, product Roughness, cutting quality and material removal rate were determined.After measuring the surface roughness on the Talysurf test device and obtaining the results, the results were analyzed in Minitab 17 software and the roughness of the EN24 (dry and wet processing) product was examined on the surface. The pathways and its contribution to decision-making ultimately indicate that it negatively affects the issue. All tests were carried out in dry and wet conditions; nine samples were produced under dry conditions and nine samples were produced under wet conditions. In this research the fundamental goal investigation of the various process(input) parameters and performed on a CNC turning machine since it is much improved in compression with different machines in context of accuracy and surface finish .The attention on the properties of the materials alongside the cutting condition of cutting tool and work piece has been made.It is found that the optimum results achieved at feed rate of 0.15 mm/rev 0.25 mm dept of cut and 2000 rpm speed.

KEYWORDS: EN24 steel alloy, RSM , Spindle speed, Feed rate, Depth of cut, Taguchi method, ANOVA,

"Optimization of Turning parameters of EN24 steel alloy using Response Surface methodology ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.g271-g288, May-2024, Available :http://www.jetir.org/papers/JETIR2405635.pdf

"Optimization of Turning parameters of EN24 steel alloy using Response Surface methodology ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppg271-g288, May-2024, Available at : http://www.jetir.org/papers/JETIR2405635.pdf