Progress Toward an Integration of Process–Structure–Property–Performance Models for “Three-Dimensional (3-D) Printing” of Titanium Alloys

• Published in: JOM (1989) Vol. 66; no. 7; pp. 1299 - 1309
• Main Authors: Collins, P. C., Haden, C. V., Ghamarian, I., Hayes, B. J., Ales, T., Penso, G., Dixit, V., Harlow, G.
• Format: Journal Article
• Language: English
• Published: Boston Springer US 01.07.2014; Springer Nature B.V
• Subjects: 3-D printers; Additive manufacturing; Bands; Chemistry/Food Science; Construction; Design; Designers; Earth Sciences; Elongation; Engineering; Environment; Heat conductivity; Integrated approach; Microstructure; Photomicrographs; Physics; Residual stress; Studies; Three dimensional models; Titanium alloys; Titanium base alloys; Modeling Activity; Constitutive Equation; Additive Manufacturing; Artificial Neural Network; Virtual Experiment
• ISSN: 1047-4838; 1543-1851
• DOI: 10.1007/s11837-014-1007-y

Electron beam direct manufacturing, synonymously known as electron beam additive manufacturing, along with other additive “3-D printing” manufacturing processes, are receiving widespread attention as a means of producing net-shape (or near-net-shape) components, owing to potential manufacturing benefits. Yet, materials scientists know that differences in manufacturing processes often significantly influence the microstructure of even widely accepted materials and, thus, impact the properties and performance of a material in service. It is important to accelerate the understanding of the processing–structure–property relationship of materials being produced via these novel approaches in a framework that considers the performance in a statistically rigorous way. This article describes the development of a process model, the assessment of key microstructural features to be incorporated into a microstructure simulation model, a novel approach to extract a constitutive equation to predict tensile properties in Ti-6Al-4V (Ti-64), and a probabilistic approach to measure the fidelity of the property model against real data. This integrated approach will provide designers a tool to vary process parameters and understand the influence on performance, enabling design and optimization for these highly visible manufacturing approaches.