Jennifer Bracken, Christopher McComb, T. Simpson, K. Jablokow
{"title":"A Review of Part Filtering Methods for Additive Manufacturing","authors":"Jennifer Bracken, Christopher McComb, T. Simpson, K. Jablokow","doi":"10.1115/detc2020-22448","DOIUrl":null,"url":null,"abstract":"\n 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 popular methods of part filtering and elaborates on the advantages and disadvantages of the various approaches. The approaches for part filtering, and the example methods, are categorized and sorted along a continuum of opportunistic and restrictive methods in order to clarify use cases for various part filtering techniques. The approaches are also examined through the lens of specificity of process, as some are designed to be process agnostic, while others are customized for a specific AM technology or even a specific AM system. Finally, current gaps that exist in the part filtering research literature are discussed to help identify necessary and promising directions for future investigation.","PeriodicalId":415040,"journal":{"name":"Volume 11A: 46th Design Automation Conference (DAC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 11A: 46th Design Automation Conference (DAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/detc2020-22448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
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 popular methods of part filtering and elaborates on the advantages and disadvantages of the various approaches. The approaches for part filtering, and the example methods, are categorized and sorted along a continuum of opportunistic and restrictive methods in order to clarify use cases for various part filtering techniques. The approaches are also examined through the lens of specificity of process, as some are designed to be process agnostic, while others are customized for a specific AM technology or even a specific AM system. Finally, current gaps that exist in the part filtering research literature are discussed to help identify necessary and promising directions for future investigation.