ANALYSIS OF SiC GRINDING WHEEL WEAR AND SURFACE ROUGHNESS IN MACHINING OF Al2O3 ADVANCED CERAMIC USING REGRESSION MODEL

P. Kanakarajan, C. Moganapriya, R. Rajasekar, S. Sundaram, M. Syed Thasthagir, S. Soundararajan and K. Manu Barath
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P. Kanakarajan: Department of Mechanical Engineering, K S R Institute for Engineering and Technology, Tiruchengode, Tamil Nadu 637215, India
C. Moganapriya: ��Department of Mining Engineering, Indian Institute of Technology, Kharagpur, West Bengal 721302, India
R. Rajasekar: ��Department of Mechanical Engineering, Kongu Engineering College, Erode, Tamilnadu 638060, India
S. Sundaram: �Department of Mechanical Engineering, Muthayammal Engineering College, Rasipuram, Tamil Nadu 637408, India
M. Syed Thasthagir: �Department of Automobile Engineering, K. S. R. College of Engineering, Tiruchengode, Tamil Nadu 637215, India
S. Soundararajan: �Department of Automobile Engineering, K. S. R. College of Engineering, Tiruchengode, Tamil Nadu 637215, India
K. Manu Barath: ��Department of Mechanical Engineering, K. S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu 637215, India

Surface Review and Letters (SRL), 2022, vol. 29, issue 06, 1-11

Abstract: Presently, there are more new kinds of requirements for the production of advanced ceramic elements in the engineering field. These ceramic elements are to be machined for a better surface roughness value. Surface roughness of the machined elements is one of the main machining characteristics which play a vital role in determining the high quality of advanced ceramic elements in engineering. In this work, some machining tests were done on the advanced aluminum oxide (Al2O3) ceramic work material using a silicon carbide (SiC) grinding wheel under different process parameters. A parametric analytical model was developed using the method of regression analysis by taking into account of four process parameters, such as depth of cut, feed, grain size and spindle speed. The effectiveness of the model is evaluated based on the comparison of experimental results with the regression analysis. The predicted values of surface roughness (Ra) and wheel wear (Ww) with minimum average error are in line to the results of the acquired experiment.

Keywords: Al2O3; SiC; surface roughness; wheel wear; regression analysis model (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0218625X22500809

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