Characterization of 3D Printers and X-Ray Computerized Tomography

TL;DR

This study evaluates and characterizes different 3D printers using X-ray computed tomography and AI-based analysis to determine optimal settings and compare print quality, surface roughness, and porosity accuracy across multiple printer models.

Contribution

It introduces a comprehensive methodology combining CT imaging and AI segmentation to assess and compare 3D printer performance and quality.

Findings

ProJet MJP produces the highest quality prints with minimal surface roughness.

Optimal print quality is achieved with 100% infill, high resolution, and low nozzle speed.

Printed samples closely match the porosity of natural samples, especially with ProJet MJP.

Abstract

The 3D printing process flow requires several inputs for the best printing quality. These settings may vary from sample to sample, printer to printer, and depend upon users' previous experience. The involved operational parameters for 3D Printing are varied to test the optimality. Thirty-eight samples are printed using four commercially available 3D printers, namely: (a) Ultimaker 2 Extended+, (b) Delta Wasp, (c) Raise E2, and (d) ProJet MJP. The sample profiles contain uniform and non-uniform distribution of the assorted size of cubes and spheres with a known amount of porosity. These samples are scanned using X-Ray Computed Tomography system. Functional Imaging analysis is performed using AI-based segmentation codes to (a) characterize these 3D printers and (b) find Three-dimensional surface roughness of three teeth and one sandstone pebble (from riverbed) with naturally deposited layers is also compared with printed sample values. Teeth has best quality. It is found that ProJet MJP gives the best quality of printed samples with the least amount of surface roughness and almost near to the actual porosity value. As expected, 100% infill density value, best spatial resolution for printing or Layer height, and minimum nozzle speed give the best quality of 3D printing.