Design, developement and validation of measurement methods and systems for the functional and performance characterisation of rapid prototyping systems for biomedical applications

The increasing use of additive manufacturing (AM) in hospital Point-of-Care (PoC) environments has highlighted the need for reliable quality control (QC) procedures for patient-specific medical models and devices. Despite the rapid diffusion of biomedical 3D printing technologies, current regulatory frameworks and technical standards remain largely oriented toward industrial manufacturing settings and do not provide harmonized protocols specifically tailored to clinical PoC workflows. In this context, this doctoral research focuses on the development of measurement-based QC methodologies for biomedical 3D printing, with particular attention to dimensional and mechanical assessment. The work first reviews the main biomedical AM technologies, including fused deposition modelling, vat photopolymerization, powder bed fusion, and material jetting, together with the current international regulatory framework. Existing standards and literature were analyzed to identify the main gaps and limitations related to QC in PoC settings. The experimental activities followed a typical hospital PoC workflow, from medical image acquisition and segmentation to printing and final inspection. Different anatomical case studies were investigated, including cranial, clavicular, and pediatric airway models produced with different technologies and materials. The dimensional assessment focused on methodologies based on diagnostic and industrial computed tomography (CT) and image analysis. The results showed that diagnostic CT systems can provide reliable dimensional information for QC purposes in hospital settings. Across different investigations, dimensional deviations of approximately 2% were consistently observed. The mechanical assessment focused on soft 3D-printable materials for surgical simulation and patient-specific applications. Tensile, dynamic mechanical analysis (DMA), and creep tests were performed on standardized and anatomically derived specimens. Trachea-shaped specimens produced by stereolithography showed a Mean Absolute Percentage Error (MAPE) of approximately 2% compared to reference values of real human tracheal tissue, indicating a close mechanical agreement. The recurrence of deviations of approximately 2% across both dimensional and mechanical assessments could suggest a preliminary quantitative reference for QC evaluation in PoC biomedical 3D printing applications. Overall, this research contributes to the development of a QC framework for biomedical 3D printing in hospital PoC environments. The proposed approach combines dimensional and mechanical verification with uncertainty analysis and practical workflow considerations, supporting the future development of harmonized and clinically feasible QC protocols.