Part filtering methods for additive manufacturing: A detailed review and a novel process-agnostic method

Jennifer Bracken Brennan, Timothy W. Simpson, Christopher McComb, Kathryn W. Jablokow, Joseph Hamann

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


As additive manufacturing (AM) increases in popularity, many companies seek to identify which parts can be produced via AM. This has led to new areas of research known as “part filtering”, “part selection”, or “part identification” for AM. Numerous methods have been proposed to quantify the suitability of a design to be made with AM, and each has its own benefits and drawbacks. This paper reviews 13 published part filtering methods and compares their advantages and disadvantages. The methods for part filtering are categorized and sorted along a continuum of opportunistic and restrictive design for AM guidelines in order to ascertain how parts are evaluated and screened. The methods are also examined through the lens of process-specificity, as some are designed to be process-agnostic, while others are customized for a specific AM technology or even a specific AM system. Based upon this analysis, a novel part filtering method is synthesized from the results, presented, and tested with practicing engineers. Testing indicates use of the method improves engineers’ ability to accurately identify suitability of part candidates for AM. This new method is designed to be process-agnostic and more comprehensive by including key criteria identified as important in the literature review. Limitations and future work are also discussed following demonstration of the new method.

Original languageEnglish (US)
Article number102115
JournalAdditive Manufacturing
StatePublished - Nov 2021

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • General Materials Science
  • Engineering (miscellaneous)
  • Industrial and Manufacturing Engineering


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