Prediction and visualization of achievable orientation tolerances for additive manufacturing

Hannah Budinoff, Sara McMains

Research output: Contribution to journalConference articlepeer-review

17 Scopus citations


In additive manufacturing, process parameters can have a large influence on the quality of the produced part, making it difficult to understand what tolerances are actually achievable. We present a system that can rapidly analyze part geometry and predict parallelism, perpendicularity, and angularity geometric deviations for planar surfaces, based on layer thickness and build direction. Our system can analyze multiple distinct features and their corresponding tolerances and datums to identify build directions where all specified tolerances can be achieved. This tool can be used to select an optimal build direction and to analyze whether specified tolerances are manufacturable using additive manufacturing.

Original languageEnglish (US)
Pages (from-to)81-86
Number of pages6
JournalProcedia CIRP
StatePublished - 2018
Externally publishedYes
Event15th CIRP Conference on Computer Aided Tolerancing, CIRP CAT 2018 - Milan, Italy
Duration: Jun 11 2018Jun 13 2018


  • Additive manufacturing
  • geometric deviations
  • tolerancing

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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