Part filtering methods for additive manufacturing

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.

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Metadata

Work Title Part filtering methods for additive manufacturing
Subtitle A detailed review and a novel process-agnostic method
Access
Open Access
Creators
  1. Jennifer Bracken Brennan
  2. Timothy W. Simpson
  3. Christopher McComb
  4. Kathryn W. Jablokow
  5. Joseph Hamann
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Additive Manufacturing
Publication Date November 1, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1016/j.addma.2021.102115
Deposited November 18, 2021

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Version 1
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  • Created
  • Added Part_Filtering_Methods_for_Additive_Manufacturing.pdf
  • Added Creator Jennifer Bracken Brennan
  • Added Creator Timothy W. Simpson
  • Added Creator Christopher McComb
  • Added Creator Kathryn W. Jablokow
  • Added Creator Joseph Hamann
  • Published
  • Updated
  • Updated
  • Updated