Predicting the Strength of EBAM 3D Printed Ti-6Al-4V from Processing Conditions

Abstract

In this study, a process-to-property linear regression model was developed to predict the yield and ultimate tensile strengths of as printed Ti-6Al-4V from electron beam additive manufacturing (EBAM). A total of 8 printing conditions such as bead width, wire feed rate, deposition speed were utilized to predict the material properties in three different notional parts produced over a period of several months. It was found that as the precision and variety of processing conditions collected during print improved between prints, so did the predictive ability of the model. In the final print, the model predicted the yield and ultimate strengths of 72 specimens with an R2 correlation of 0.8 and 0.6 for the horizontal and vertical test specimens, respectively. Although the current model indirectly accounted for thermal fluctuations, further improvements to the model’s ability to predict material strength are expected with the addition of thermal data captured in subsequent notional parts.

Keywords

• additive manufacturing
• direct energy deposition
• manufacturing
• processing conditions
• Ti-6Al-4V
• titanium