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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM31760

Optimization of Surface Roughness in Turning of Wet & Dry Condition of Alloy Steel Using Taguchi Method

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM31760

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AK

Abhilash Kumar

APT

Akhilesh Pati Tiwari

R

Rone

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Abstract

The present work is aimed at studying the performance in turning of alloy steel by using performance investigators on surface roughness. In alloy steel machining tool life is greatly affected by the following cutting parameters: Spindle speed peed, depth of cut and feed. Taguchi ‘s orthogonal array L9 is found to be the best suitable method for this experiment of both wet and dry turning. It is decided to use three levels for each factor. Also signal to noise ratio results and analysis are discussed. For each experimental value, three set of trials are performed and the average value is recorded as the final. Minitab software version 17 is used to optimization the experimental plan for Taguchi technique. The techniques are used to analyse optimum objective functions, minimum surface roughness. The experiments are conducted in dry and wet turning process using CNC machine. The work pieces used for the experiments were of diameter 45 mm and length 145 mm. In this study, the most effected parameters on surface roughness were feed rate. The experiments are planned in the design of experiments (DoE), which facilitates a smaller number of experiments to obtain the desired output.

KEYWORDS

Turning Orthogonal array roughness spindle Taguchi Method Signal-to-noise.

Cite This Article

Abhilash Kumar, Akhilesh Pati Tiwari, Rone, "Optimization of Surface Roughness in Turning of Wet & Dry Condition of Alloy Steel Using Taguchi Method," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024.

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12/31/45421

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