Harnessing process variables in additive manufacturing for design using manufacturing elements

Yi Xiong, Yunlong Tang, Sang-In Park, David W. Rosen

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Process plans in additive manufacturing (AM) have a profound impact on the performance of fabricated parts such as geometric accuracy and mechanical properties. Due to its layer-based, additive nature, AM processes can be controlled at multiple scales starting from the scan vector/pixel scale. However, most process planning methods in AM configure process settings at the part scale. This leaves large unexplored regions in the design space that may include optimal designs. To address these untapped potentials, we present a process planning strategy based on the concept of manufacturing elements (MELs) to harness process variables at low scales for design. First, we decompose a part design into multiple MELs that contain geometric and manufacturing information. Two-scale process-structure-property (PSP) relationships are then constructed for MELs and their assembly. Decision tools, including the compromise decision support problem, are employed to navigate two-scale PSP relationships for supporting designers in design exploration on process variables and optimization of process plans. The proposed strategy is illustrated with a process planning example for a lattice structure, which has multiple design goals and is to be fabricated using material extrusion.

Original languageEnglish
Article number072002
Number of pages11
JournalJournal of Mechanical Design
Volume142
Issue number7
DOIs
Publication statusPublished - Jul 2020
Externally publishedYes

Keywords

  • Computer-aided design
  • Data-driven design
  • Decision theory
  • Design exploration
  • Design for additive manufacturing
  • Design for X
  • Design methodology
  • Design theory
  • Manufacturing element
  • Methodology
  • Process planning

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