Segmented time series visualization tool for additive manufacturing

Abstract

Additive manufacturing promises to deliver the ability to build complex shapes and parts while using raw materials more efficiently than traditional manufacturing approaches. However, material scientists are continually striving to understand how complex build parameters affect the 3D printing process and the quality of the final product. Understanding the intricate relationships between parameters and final product will yield the opportunity for automatic tuning of variables to ensure consistency of quality across build iterations.