Indian Journal of Engineering & Materials Sciences

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Neural network modeling of forces in drilling of glass/epoxy composites filled with agro-based waste materials


Affiliations
1 Shree Guru Gobind Singh Tricentenary University, Gurugram – 122 505, India
2 Department of Mechanical Engineering, National Institute of Technology Meghalaya, Shillong – 793 003, India
3 Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee – 247 667, India
4 Department of Mechanical Engineering, Guru Nanak Dev Engineering College, Ludhiana – 141 006, India

In this paper, the drilling behavior of a new class of composite materials has been experimentally investigated. The composite laminates have been manufactured using glass fibers, epoxy resin, and filler materials. The abundantly available agro-based waste materials (coconut coir, rice husk, and wheat husk) have been used as filler materials. The drilling experiments have been performed at several levels of feed (0.03 to 0.3 mm/rev.) and speed (90 to 2800 RPM) using different types of drill bits. The effect of these parameters on the drilling forces (axial thrust and torque) has been analyzed for all types of laminates under investigation. The artificial neural network-based models have also been proposed to compute the drilling forces. The fitness of the models has been measured in terms of mean percentage error between the predicted and actual values. From the investigation, it has been found that the drilling forces computed by the neural network models were quite close to the experimental values.
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  • Neural network modeling of forces in drilling of glass/epoxy composites filled with agro-based waste materials

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Authors

Vikas Dhawan
Shree Guru Gobind Singh Tricentenary University, Gurugram – 122 505, India
Kishore Debnath
Department of Mechanical Engineering, National Institute of Technology Meghalaya, Shillong – 793 003, India
Inderdeep Singh
Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee – 247 667, India
Sehijpal Singh
Department of Mechanical Engineering, Guru Nanak Dev Engineering College, Ludhiana – 141 006, India

Abstract


In this paper, the drilling behavior of a new class of composite materials has been experimentally investigated. The composite laminates have been manufactured using glass fibers, epoxy resin, and filler materials. The abundantly available agro-based waste materials (coconut coir, rice husk, and wheat husk) have been used as filler materials. The drilling experiments have been performed at several levels of feed (0.03 to 0.3 mm/rev.) and speed (90 to 2800 RPM) using different types of drill bits. The effect of these parameters on the drilling forces (axial thrust and torque) has been analyzed for all types of laminates under investigation. The artificial neural network-based models have also been proposed to compute the drilling forces. The fitness of the models has been measured in terms of mean percentage error between the predicted and actual values. From the investigation, it has been found that the drilling forces computed by the neural network models were quite close to the experimental values.