Neural network-based modeling of FFF process for PET-G: Evaluating MLPNN and RBFNN performance in mechanical property prediction

Sourabh Anand, Manoj Kumar Satyarthi, University School of Information, Communication and Technology, Guru Gobind Singh Indraprastha University, New Delhi

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering

Published online on August 23, 2024

Abstract

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Ahead of Print.
PET-G is a versatile thermoplastic resistant to impact loading, heat, and reactivity with solvents, and witnesses wide use in the Display and Signage, Packaging, Automotive, Electronics, and Medical Industries. Customized production using conventional ...