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Drilling Studies on Sustainable Lightweight Hybrid Polymer Matrix High-Performance Nanocomposites Saveetha School of Engineering, SIMATS
- Format:
- Book
- Conference/Event
- Author/Creator:
- Senthilkumar, N., author.
- Conference Name:
- AeroCON 2026 (2026-06-04 : Bangalore, India)
- Language:
- English
- Subjects (All):
- Lightweight materials.
- Molding.
- Machine learning.
- Nanomaterials.
- Machining processes.
- Drilling.
- Polymers.
- Composite materials.
- Fibers.
- Joining.
- Local Subjects:
- Lightweight materials.
- Molding.
- Machine learning.
- Nanomaterials.
- Machining processes.
- Drilling.
- Polymers.
- Composite materials.
- Fibers.
- Joining.
- Physical Description:
- 1 online resource
- Place of Publication:
- Warrendale, PA SAE International 2026
- Summary:
- Worldwide, engineers are exploring the possibility of using polymer composites in their quest for lightweight materials. In this study, injection moulding was used to develop a biodegradable polymer PLA composite containing 20 wt.% vetiver fibers (VFs) and 2 wt.% nano-silica (nSiO2) obtained from pearl millet, which is sustainable. Materials need machining as secondary operation that required joining. Desirability analysis was used to examine and optimize machining (drilling) studies that were designed with Taguchi's design (L9 orthogonal array). Surface roughness (SR) and delamination factor (Fd) were taken as outputs, while spindle speed (SS), feed rate (FR), and drill diameter (DD) were the inputs. Drilling studies were performed on a single vertical machining center (VMC). ANOVA identifies that the FR had the most decisive influence on SR (F=559.24, p=0.001785), followed by DD and SS. FR is the dominant contributor to Fd (F=379, p=0.00263), followed by SS and DD. At low SS and high FR, excessive thrust and heat cause fiber-matrix tearing and poor hole finish. Higher SS softens the PLA matrix, improving surface quality. Fd decreases with increasing SS, whereas it rises with extreme FR and DD due to elevated thrust and matrix cracking. The optimized parameters SS of 3000 rpm, FR of 15 mm/min, and DD of 6 mm achieved a maximum combined desirability of 1. A non-traditional meta-heuristic technique, the frog leaping algorithm (FLA), is adopted to optimize the inputs based on the developed regression model. FLA also provides the identical optimal condition as the desirability function, predicting the outputs SR=2.2195 μm and Fd=1.0383, which are very close
- Notes:
- Vendor supplied data
- Access Restriction:
- Restricted for use by site license
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