The webinar is a project closeout presentation for the GE Global Research led effort which developed a method and model for predicting laser powder fed directed energy deposition tensile properties of Ti-6Al-4V. The project is titled, “MAMLS Feature-Based Qualification Method for Directed Energy Deposition AM”.
Recognizing it can take several years to go from concept to production for additively manufactured components, this project leverages a feature based qualification method to decompose a complex and relevant aerospace structure for the purposes of reducing the cost and time for DED process qualification. A method to develop and validate a Bayesian Hybrid Modeling framework which predicts tensile mechanical properties for an array of aerospace application relevant geometric features will be presented. The team’s approach included the systematic decomposition of a geometrically complex component into several critical “features”, experimental process development of Ti-6Al-4V DED of these features, development of a model which can predict tensile properties (or the necessary processing conditions to obtain said mechanical properties) using a bidirectional hybrid modeling framework, and utilization of Intelligent Design Analysis of Computer Experiments for the purposes of reducing model uncertainty.
A discussion of the approaches accuracy to predicting tensile mechanical properties, recommendations for process parameters to obtain target tensile properties, and opportunities for realizing cost and time savings as a result of these efforts will be delivered.