Investigation of wear rate of FDM printed TPU, ASA and multi-material parts using heuristic GANN tool

Abstract

The present work deals with analysing the wear behavior of parts fabricated using thermoplastic polyurethane (TPU), acrylonitrile styrene acrylate (ASA), and multi-materials (TPU + ASA) polymers manufactured at significant process parameters of fused deposition modelling, i.e., infill density, speed, wall thickness, raster angle, temperature. ASTM G99 standard test parts are fabricated at various process parameters of the extrusion-based FDM 3D printer to investigate their wear strength. Wear testing has been done using the DUCOM TR-20LE pin-on-disc wear testing apparatus to investigate wear rate. Thirty-eight experiments have been performed based on central composite design on the pin on the disc machine with different materials, and output response is recorded as wear strength. An artificial intelligent model between input and output parameters is developed with NN (Neural Network), and further, it is optimized with the help of the heuristic tool GA (Genetic Algorithm). It is observed that the least wear rate for multi-material (material density 1.14 g/cm3) achieved is 0.3880 mm3/m; at raster angle 45°, infill density 40%, extrusion temperature 240 °C, speed 46.667 mm/s, and wall thickness 0.8 mm and same has been validated experimentally.