Manufacturing Commons^™

A Machine Learning Method For The Prediction Of Melt Pool Geometries Created By Laser Powder Bed Fusion, Jonathan Ciaccio

University of New Orleans Theses and Dissertations

A machine learning model is created to predict melt pool geometries of Ti-6Al-4V alloy created by the laser powder bed fusion process. Data is collected through an extensive literature survey, using results from both experiments and CFD modeling. The model focuses on five key input parameters that influence melt pool geometries: laser power, scanning speed, spot size, powder density, and powder layer thickness. The two outputs of the model are melt pool width and melt pool depth. The model is trained and tested by using the k fold cross validation technique. Multiple regression models are then applied to find the …

Silver Microparticle And Submicron Wire - Polylactic Acid Composites For Additive Manufacturing, Jenna W. Robichaux

University of New Orleans Theses and Dissertations

This thesis explores the incorporation of silver microparticle and submicron wire additives into thermoplastic filament feedstock for fused filament fabrication (FFF) to create multifunctional three-dimensional (3D) printable composites. The impact of silver microparticle and submicron wire additives on mechanical behavior along with antibacterial effect of the silver microparticle and submicron wire additives on printed objects were assessed.

Composite FFF filaments were fabricated by solution processing, granulation, and extrusion. Differential Scanning Calorimetry (DSC) was conducted to measure the glass transition and melting point temperatures of the composite filaments for 3D printing. The effect of the additive addition on the thermal properties …