Experimental evaluation and prediction on drilling of Corchorus olitorius filler-based composite

ABSTRACT

Naturally derived fibers/fillers-based polymers have gained much attention in many industrial applications due to the requirement for renewable and biodegradable components. Machining is sometimes needed to simplify the assembly of pieces in a finished product. Here, this article reports how drill machining affects polymer composites made with 5 wt.% jute filler that has undergone alkaline treatment. The experimental tests have been conducted to explore the impact of tool bit diameter, cutting speed and feed on the various generated responses (thrust force, surface roughness, delamination peel-up and delamination push-out). The results reveal that the appropriate responses are achieved when the cutting speed of the tool is at its maximum while the feed and tool diameter are at their minimal amounts. The response surface methodology (RSM) and support vector machine (SVM) algorithms have been devised to anticipate the drilling performance of produced composites, and both strategies have shown high agreement with experimentally acquired findings. However, the ML tool algorithm proven more reliable than RSM models because of the superior correlation of determination coefficients.

GRAPHICAL ABSTRACT

KEYWORDS:

• Natural fibers
• composite
• machining
• delamination
• microstructure analysis
• RSM
• Machine Learning

Acknowledgments

The authors would like to thank the Machine Element Laboratory, NIT Silchar for their assistance in carrying out this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The study presented in the article made no use of data.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.