Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.3960
Publisher URL: https://www.epubli.de/shop/buch/Adapting-to-the-Future-Christian-M-Ringle-Thorsten-Blecker-Wolfgang-Kersten-9783754927700/121489
Title: How to apply artificial intelligence in the additive value chain : a systematic literature review
Language: English
Authors: Brylowski, Martin 
Schwieger, Lea-Sophie 
Nagi, Ayman  
Kersten, Wolfgang  
Editor: Kersten, Wolfgang  
Ringle, Christian M.  
Blecker, Thorsten 
Keywords: Artificial Intelligence;Blockchain
Issue Date: 1-Dec-2021
Publisher: epubli
Source: Hamburg International Conference of Logistics (HICL) 31: 65-100 (2021)
Part of Series: Proceedings of the Hamburg International Conference of Logistics (HICL) 
Volume number: 31
Abstract (english): 
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.
Conference: Hamburg International Conference of Logistics (HICL) 2021 
URI: http://hdl.handle.net/11420/11175
DOI: 10.15480/882.3960
ISBN: 978-3-754927-70-0
ISSN: 2365-5070
Institute: Logistik und Unternehmensführung W-2 
Document Type: Chapter/Article (Proceedings)
Peer Reviewed: Yes
License: CC BY-SA 4.0 (Attribution-ShareAlike 4.0) CC BY-SA 4.0 (Attribution-ShareAlike 4.0)
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