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

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.

Automated summary

As additive manufacturing (AM) becomes more popular, companies are seeking to identify parts that can be produced using AM. This paper reviews and compares 13 published part filtering methods, categorizing and sorting them while examining them through the lens of process specificity. A new part filtering method is proposed and tested, showing improvements in engineers' ability to identify suitable parts for AM.