Shape deviation modeling for fused deposition modeling processes

Suoyuan Song, Andi Wang, Qiang Huang, Fugee Tsung

Research output: Contribution to journalConference articlepeer-review

22 Scopus citations

Abstract

3D Printing or Additive Manufacturing (AM), refers to a new class of technologies of making products directly from any three-dimensional digital models. Broader applications of AM require to lower the cost of AM machines. However, products fabricated by low-end machines suffer from the issue of low dimensional accuracy. In this paper, we intend to address this issue for Fused Deposition Modeling (FDM) process- one of mostly adopted AM technologies. Based on the FDM mechanism, we attribute the dimensional inaccuracy to two significant error sources that affect the shape of the product consecutively: (i) positioning error of the extruder and (ii) shape deformation induced by processing error including phase change and other variations occurred. We first adopt Kriging method to model the extruder positioning error, which is treated as design input error under a novel framework of modeling the product shape deformation. Experimental results and case studies demonstrate the effectiveness of the predictive modeling framework, which can be applied to compensate dimensional error of 3D printed products.

Original languageEnglish (US)
Article number6899411
Pages (from-to)758-763
Number of pages6
JournalIEEE International Conference on Automation Science and Engineering
Volume2014-January
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 IEEE International Conference on Automation Science and Engineering, CASE 2014 - Taipei, Taiwan, Province of China
Duration: Aug 18 2014Aug 22 2014

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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