@masterthesis{Bhatt2025, type = {Bachelor Thesis}, author = {Bhatt, Revant Nitin}, title = {Characterization and Optimization of Process Parameters for Polycaprolactone-based Medical Scaffolds for a Magnetic Planar Drive-based 3D Printer}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-22330}, school = {Hochschule Rhein-Waal}, pages = {71}, year = {2025}, abstract = {This thesis investigates the optimization of process parameters for a Magnetic Planar Drive (MPD)-based 3D printer to fabricate Polycaprolactone (PCL) scaffolds for medical applications. The study aims to identify an optimal set of parameters that ensures high-dimensional accuracy while maintaining structural integrity. A systematic experimental methodology was adopted, beginning with a full-factorial design to establish baseline parameters for printing temperature (170°C), printing speed (15 mm/s), and nozzle diameter (0.4 mm). A Box-Behnken Design (BBD) was employed to optimize critical parameters, specifically layer height, raster width, and mover levitation height. Analysis of Variance (ANOVA) identified layer height as the most dominant factor influencing dimensional accuracy (p < 0.0001), while raster width and mover levitation had lesser effects. The experimental validation of the optimization results revealed discrepancies between the numerically and empirically optimized parameter sets. Although the numerically optimized settings had a theoretically superior accuracy of 98.29\%, their practical implementation led to structural failures, specifically the collapse of scaffold bridges. In contrast, the empirically optimized set (layer height: 0.2 mm, raster width: 0.45 mm, mover levitation height: 2.25 mm) consistently achieved a mean dimensional accuracy of 97.14\% while maintaining stable printability. The findings demonstrate the potential of MPD-based 3D printing for fabricating medical scaffolds and establishing a validated parameter set.}, language = {en} }