Article Number: DRJEIT7391583602
ISSN: 2354-4155

Vol. 9 (4), Pp. 192-200, May 2022

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Creative Commons Attribution License 4.0.

Original Research Article

The Effect of Parameters and Optimization of Surface Roughness and Cutting Temperature in Turning of AISI 1020 Carbon Steel using Taguchi Technique and ANOVA

Ososomi, A. S*.

Ekhayeme, M. O.


Quality and productivity play significant role in today’s manufacturing market. In this research work, turning operation is performed on mild steel aimed at evaluating the best process environment which could simultaneously satisfy requirements of both quality and as well as productivity. Here we conducted experiments by taking Cutting Speed, Feed Rate & Depth of cut as process parameters and got the optimized value of Surface Roughness and Cutting temperature. An L9 orthogonal array, the signal-to-noise (S/N) ratio and the analysis of variance (ANOVA) are employed to the study the performance characteristics in the turning on CNC using tungsten coated carbide cutting tool insert with a nose radius of 0.8mm. The analysis of results shows that the combination of process parameters for minimum surface roughness is obtained at 75m/min cutting speed, 0.2 mm/rev feed and 1.0 mm depth of cut for minimum surface roughness. It is observed that feed rate and the speed plays important role in minimizing surface roughness. For maximum material removal rate, the optimum values are cutting speed of 75m/min, feed rate of 0.2 mm/ rev and depth of cut of 0.6 mm. It is also observed that depth of cut and the speed plays important role in minimizing cutting temperature. Finally, the relationship between cutting parameters and responses were developed by using the Minitab 18.1 software and regression equations were developed. For surface roughness and cutting temperature, the values of 2.313  and 65.390C were determined using their respectively objective functions with their optimum parameters (values).

Keywords: Taguchi, ANOVA, signal to noise ratio, Minitab, insert, cutting temperature and surface roughness

 Received: April 19, 2022  Accepted: May 10, 2022  Published: May 18, 2022

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