Optical Methods of Error Detection in Additive Manufacturing: A Literature Review
Additive Manufacturing (AM) has been a growing industry, specifically when trying to mass produce products more cheaply and efficiently. However, there are too many current setbacks for AM to replace traditional production methods. One of the major problems with 3D printing is the high error rate co...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Journal of Manufacturing and Materials Processing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-4494/7/3/80 |
| _version_ | 1797593996749438976 |
|---|---|
| author | Brianna Wylie Carl Moore |
| author_facet | Brianna Wylie Carl Moore |
| author_sort | Brianna Wylie |
| collection | DOAJ |
| description | Additive Manufacturing (AM) has been a growing industry, specifically when trying to mass produce products more cheaply and efficiently. However, there are too many current setbacks for AM to replace traditional production methods. One of the major problems with 3D printing is the high error rate compared to other forms of production. These high error rates lead to wasted material and valuable time. Furthermore, even when parts do not result in total failure, the outcome can often be less than desirable, with minor misprints or porosity causing weaknesses in the product. To help mitigate error and better understand the quality of a given print, the field of AM monitoring in research has been ever-growing. This paper looks through the literature on two AM processes: fused deposition modeling (FDM) and laser bed powder fusion (LBPF) printers, to see the current process monitoring architecture. The review focuses on the optical monitoring of 3D printing and separates the studies by type of camera. This review then summarizes specific trends in literature, points out the current limitations of the field of research, and finally suggests architecture and research focuses that will help forward the process monitoring field. |
| first_indexed | 2024-03-11T02:17:24Z |
| format | Article |
| id | doaj.art-717ac17a5ca24876ba1e709095f40875 |
| institution | Directory Open Access Journal |
| issn | 2504-4494 |
| language | English |
| last_indexed | 2024-03-11T02:17:24Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Manufacturing and Materials Processing |
| spelling | doaj.art-717ac17a5ca24876ba1e709095f408752023-11-18T11:05:14ZengMDPI AGJournal of Manufacturing and Materials Processing2504-44942023-04-01738010.3390/jmmp7030080Optical Methods of Error Detection in Additive Manufacturing: A Literature ReviewBrianna Wylie0Carl Moore1Department of Mechanical Engineering, Florida A&M University, CISCOR Lab, FAMU-FSU College of Engineering, Tallahassee, FL 32310, USADepartment of Mechanical Engineering, Florida A&M University, CISCOR Lab, FAMU-FSU College of Engineering, Tallahassee, FL 32310, USAAdditive Manufacturing (AM) has been a growing industry, specifically when trying to mass produce products more cheaply and efficiently. However, there are too many current setbacks for AM to replace traditional production methods. One of the major problems with 3D printing is the high error rate compared to other forms of production. These high error rates lead to wasted material and valuable time. Furthermore, even when parts do not result in total failure, the outcome can often be less than desirable, with minor misprints or porosity causing weaknesses in the product. To help mitigate error and better understand the quality of a given print, the field of AM monitoring in research has been ever-growing. This paper looks through the literature on two AM processes: fused deposition modeling (FDM) and laser bed powder fusion (LBPF) printers, to see the current process monitoring architecture. The review focuses on the optical monitoring of 3D printing and separates the studies by type of camera. This review then summarizes specific trends in literature, points out the current limitations of the field of research, and finally suggests architecture and research focuses that will help forward the process monitoring field.https://www.mdpi.com/2504-4494/7/3/80additive manufacturing3D Printingartificial intelligenceoptical monitoringliterature review |
| spellingShingle | Brianna Wylie Carl Moore Optical Methods of Error Detection in Additive Manufacturing: A Literature Review Journal of Manufacturing and Materials Processing additive manufacturing 3D Printing artificial intelligence optical monitoring literature review |
| title | Optical Methods of Error Detection in Additive Manufacturing: A Literature Review |
| title_full | Optical Methods of Error Detection in Additive Manufacturing: A Literature Review |
| title_fullStr | Optical Methods of Error Detection in Additive Manufacturing: A Literature Review |
| title_full_unstemmed | Optical Methods of Error Detection in Additive Manufacturing: A Literature Review |
| title_short | Optical Methods of Error Detection in Additive Manufacturing: A Literature Review |
| title_sort | optical methods of error detection in additive manufacturing a literature review |
| topic | additive manufacturing 3D Printing artificial intelligence optical monitoring literature review |
| url | https://www.mdpi.com/2504-4494/7/3/80 |
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