Statistical modelling and assessment of surface roughness in drilling of hybrid fiber composite

Authors

  • David, A. G., Ramalingam, V. S., Chandran, A. P., Ramachandran, A., & Selvam, A. Author

Abstract

In this article, the effects of conventional drilling parameters on the surface roughness of holes in hybrid fibre composites were investigated and quantified. A sample of a hybrid fibre composite with E-glass, hemp, and flax fibre reinforcements was fabricated by the hand lay-up method and subjected to drilling tests under different operating conditions by varying the drilling process parameters (drill diameter, spindle speed, and feed rate). The average surface roughness (Ra in µm) of the drilled hole was measured for each set of conditions. The results were subjected to statistical analysis (ANOVA) to determine the effects of process parameters on the measured variable. The calculations show that a combination of drill diameter and spindle speed, as well as drill diameter and feed rate, are the most important determinants of variation in bore surface roughness. A simple regression equation with linear terms was then established to model the observed interactions between the input and output variables. The equation was able to accurately model the behaviour of surface roughness, showing that this methodology can be extrapolated for use with different machining processes and/or materials. The 3-factor analysis ANOVA, performed with a confidence level of 95% and a statistical significance of a p-value less than 0.05, showed that the drill diameter ranked first and made the largest contribution (82.394% contribution), followed by the feed rate (16.719% contribution) and the spindle speed (0.6199% contribution). Regression modelling using linear regression yielded an R2 value of 0.8015 and using the power-law equation yielded an R2 value of 0.8796.

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Published

2023-07-15

Issue

Section

Articles

How to Cite

Statistical modelling and assessment of surface roughness in drilling of hybrid fiber composite. (2023). Multidisciplinary Science Journal, 6(2). https://malquepub.com/index.php/multiscience/article/view/126