Dr. Pum Kim
Manufacturing Science Division
Oak Ridge National Laboratory

Lattice Structure Design and Manufacturing for 3D Printing

ABSTRACT: Recent development of additive manufacturing, also known as 3D printing, enabled geometrically complex structures including various lattice shapes to be fabricated which was challenging previously through conventional manufacturing methods. Due to the design flexibility of 3D printing, the geometry of the lattice structures can be tailored for high performance. We have developed algorithms to develop functionally graded lattice (FGL) structures for 2D and 3D with varying cell sizes, which is different from conventional FGLs with varying thicknesses. These lattice designs involve many stop/start movements of nozzle which often lead to defects and printing failure. We have developed an algorithm to create continuous path lines for given lattice designs without stop/start movements. This presentation will discuss about designing functionally graded lattice structures, creating toolpaths for the lattices with continuous path lines, performance prediction techniques through finite element analysis, and a reverse design approach using machine learning.

BIOGRAPHY: Dr. Seokpum (Pum) Kim is leading simulation-assisted digital manufacturing efforts for polymer composites. His research involves integrating computational prediction tools, sensor and monitoring data, and machine learning to optimize manufacturing processes and to optimize design for polymer composites. He has published multiple papers (>10 articles in 2022 alone), patents, and reports in polymer composite manufacturing.