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How to apply artificial intelligence in the additive value chain : a systematic literature review
Citation Link: https://doi.org/10.15480/882.3960
Publikationstyp
Conference Paper
Date Issued
2021-12-01
Sprache
English
Author(s)
Herausgeber*innen
TORE-DOI
First published in
Number in series
31
Start Page
65
End Page
100
Citation
Hamburg International Conference of Logistics (HICL) 31: 65-100 (2021)
Contribution to Conference
Scopus ID
Publisher
epubli
Peer Reviewed
true
Purpose: Additive manufacturing (AM) enables the manufacturing of metal parts and is therefore increasingly important for industry. Unfortunately, the manufactured parts exhibit many imperfections, such as faults or other quality defects. The use of artificial intelligence (AI) allows for the steady optimization of processes, making its potential implementation in AM interesting as it could help to improve processes for industrialization and serial production.
Methodology: A systematic review was conducted of the literature on applications of AI in AM. A total of 741 articles published between 2008 and 2020 were scanned to determine whether they described an explicit application of AI in a metalworking process. A detailed analysis yielded 87 relevant sources.
Findings: The articles were scanned for existing application areas of AI in AM, including application in the associated value chain phases of AM planning and AM execution. In AM planning, AI is frequently used to support the design process, while in AM execution, AI is mostly used for process monitoring and defect detection.
Originality: The applications of AI in AM were investigated by means of a systematic literature review. The resultant findings should provide insights into existing and potential application areas for AI in AM.
Methodology: A systematic review was conducted of the literature on applications of AI in AM. A total of 741 articles published between 2008 and 2020 were scanned to determine whether they described an explicit application of AI in a metalworking process. A detailed analysis yielded 87 relevant sources.
Findings: The articles were scanned for existing application areas of AI in AM, including application in the associated value chain phases of AM planning and AM execution. In AM planning, AI is frequently used to support the design process, while in AM execution, AI is mostly used for process monitoring and defect detection.
Originality: The applications of AI in AM were investigated by means of a systematic literature review. The resultant findings should provide insights into existing and potential application areas for AI in AM.
Subjects
Artificial Intelligence
Blockchain
DDC Class
330: Wirtschaft
Publication version
publishedVersion
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Brylowski et al. (2021) - How to apply Artificial Intelligence in the Additive Value Chain A Systematic Literature Review.pdf
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