Development of an integrated testing and calibration approach for fused filament fabrication of polylactic acid

Abstract

The Fused Filament Fabrication (FFF) technique faces challenges in mitigating defects generated in the printing process for the quality assurance of final products. To address this, accurate defect detection and identification methods are essential to use. In addition to finding ways to improve the quality and performance of FFFprinted parts, a test artefact offers a solution for identifying potential defects effectively, but it was not developed and implemented systematically yet. This study develops an integrated testing and calibration approach for mitigating defects in the FFFprinted polymer products with a new unified test artefact. This new test artefact incorporates all-in-one calibration functions, including defect identification, measurement, evaluation, and compensation. Specifically, a fitting kit is developed as part of the unified test artefact for tolerance measurement purposes with minimal effort to provide prompt feedback. Artificial Neural Network (ANN) is employed to accelerate the evaluation process for batch processing data. The devised approach and the test artefact are validated through its practical implementations into FFF of polylactic acid (PLA) and compared to other existing test artefacts in literature. Finally, a detailed defect mitigation process is highlighted via printing a PLA bevel gear set and a universal joint and significant improvements are achieved with successfully mitigating key defects.