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Parametric Optimization In Drilling Process Parameters For Machining Of Glass Fibre Reinforced Composites Using Grey Relational Grade Analysis


Paper Type 
Contributed Paper
Title 
Parametric Optimization In Drilling Process Parameters For Machining Of Glass Fibre Reinforced Composites Using Grey Relational Grade Analysis
Author 
Thirumalai Ramanathan, Kannan Sithan, Subbarayan Ramanathan and Prakash Ramasamy
Email 
vkrthirumalai@gmail.com
Abstract:

     The aim of the research is to optimize the drilling process parameters while drilling of glass fi bre reinforced composites using solid carbide drill by integrating response surface methodology and Taguchi technique. Drilling process parameters includes cutting speed, Feed rate and point angle with three levels. The responses measured against these drilling parameters are; material removal rate, surface roughness, oversize and delamination factor. The ANOVA analysis is carried out for the responses and the regression equations are developed and checked for its adequacy. The R-squared value for material removal rate is found to be 99.40%, for surface roughness is found to be 96.81% , for over size is found to be 98.2% and for delamination factor is found to be 96.46% and these values are acceptable. Also Taguchi grey relational grade analysis is carried and the grey relational coeffi cients are determined and they are ranked. The optimal parameter is fi nally determined using the grey relational analysis and the experiments are validated.

Start & End Page 
1428 - 1443
Received Date 
2022-06-22
Revised Date 
2022-07-06
Accepted Date 
2022-07-08
Full Text 
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Keyword 
grey relational coefficient, ANOVA, drilling parameters, surface roughness, GFRP composite
Volume 
Vol.49 No.5 (September 2022)
DOI 
https://doi.org/10.12982/CMJS.2022.091
Citation 
Ramanathan T., Sithan K., Ramanathan S. and Ramasamy P., Parametric Optimization In Drilling Process Parameters For Machining Of Glass Fibre Reinforced Composites Using Grey Relational Grade Analysis, Chiang Mai J. Sci., 2022; 49(5): 1428-1443. DOI 10.12982/CMJS.2022.091.
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Chiang Mai Journal of Science

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