Multi-objective optimization of 3D printing parameters to fabricate TPU for tribological applications

Abstract

Nowadays, polymers frequently replace metals in several applications where comparable properties are desired due to the convenience of processing them as per the requirement. The present work intends to fabricate a thermoplastic polyurethane suitable for journal bearing application using fused deposition modelling (FDM) additive manufacturing method. The cylindrical samples were prepared for experiments using central composite design to examine the effect of FDM machine parameters (such as layer thickness, infill density, and printing speed) on response such as specific wear rate (SWR), coefficient of friction (COF) and hardness. Layer thickness was noticed to be the most significant parameter for the selected responses with a percentage contribution of ∼34% to 72%. Further, as observed from interaction plots the COF and SWR are lowest, and hardness is highest at highest infill density and lowest printing speed. To obtain an optimized set of FDM machine parameters for minimum SWR, COF and maximum hardness, genetic algorithm based multi-objective optimization is performed. The optimized values are SWR of 4.97 × 10−5 mm3/N-m, COF of 0.37 and hardness value of 37.