A modular framework to obtain representative microstructural cells of additively manufactured parts

Abstract

The repeating nature of additive manufacturing (AM) translates into quasi-periodic repeating hierarchical microstructures, which vary depending on the working principle of the AM technology. The geometry and internal characteristics of these repeating microstructures affect the geometrical accuracy and mechanical properties of AM parts. We propose a modular and generic framework for AM microstructures to automatically determine a representative microstructural cell with average shape and microstructural information based on micrograph processing and morphological shape analyses. A general microstructural mapping procedure is presented to map and average different microstructural features inside the representative cell. Moreover, an extension of the method is proposed to recover a representative cell with a periodic shape as required for subsequent numerical micromechanical simulations under periodic boundary conditions to unravel process-structure–property relationships. The framework is demonstrated on a virtually generated microstructure and on the metallic and polymeric microstructure of two parts manufactured with different AM processes, showing the framework's versatility for different materials and AM technologies. The three test cases show the framework's modularity, where different procedures were applied to overcome the challenges of each particular case while keeping the primary method the same. We also discuss applications of the framework, such as enabling statistical investigations of spatial variations of the microstructural features across AM parts and providing essential input for microstructural and mechanical numerical simulations.

Keywords

• Additive manufacturing
• Repeating microstructures
• Representative microstructural cell
• Image processing
• Representative volume element