Analyzing and optimizing fused deposition modeling parameters for dimensional accuracy of microturbine impellers

Additive manufacturing (AM) processes are gaining widespread applications due to their ability to produce complex parts with reduced lead times. Fused deposition modeling (FDM), a promising AM process, demands precise control over its process parameters to optimize the performance. This article investigates the impact of FDM process parameters on dimensional accuracy of a microturbine impeller used in an organic rankine cycle (ORC). A full factorial design was employed to analyze the impact of FDM parameters including layer thickness, infill density, and infill angle. Dimensions of the impeller were measured using a coordinate measuring machine (CMM), and these experimental results were further used to establish the relationship between process parameters and dimensional accuracy. The adequacy of a developed predictive quadratic regression model was verified through analysis of variance (ANOVA). Individual and interaction effects of selected parameters were identified and discussed. The analysis revealed that layer thickness is significantly impacting the dimensional accuracy. Further, response surface methodology (RSM) was used to optimize the FDM process for enhanced dimensional accuracy. This study presents a significant method to enhance the adoption of the FDM process for manufacturing complex and functional parts.