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Progress in Additive Manufacturing
Erschienen in: Progress in Additive Manufacturing 2/2021

16.03.2021 | Review Article

Additive manufacturing embraces big data

verfasst von: Kaiming Bi, Dong Lin, Yiliang Liao, Chih-Hang Wu, Pedram Parandoush

Erschienen in: Progress in Additive Manufacturing | Ausgabe 2/2021

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Abstract

Additive manufacturing (AM) is a relatively novel method to fabricate 3D objects by adding layer-upon-layer materials. As one of the most anticipated techniques in recent years, AM already made advances in design, production, and supply chain process of the manufacturing industry. AM is a digital manufacturing technology in which a massive amount of data is generated during the process. Accordingly, obtaining useful information from these data to improve current AM technology becomes a challenge. Meanwhile, Big Data research provides an ideal solution for dealing with the massive data obtained from AM processes. Besides the contributions in the AM research and production, Big Data analysis methods can also be used to help designers and engineers by collecting valuable information from clients and customers. From a business perspective, the manufacturing sector will benefit from the established Big Data sharing platform to promote and popularize new products. On the other hand, customers will obtain desired commodities with the help of a new-type 3D printing service system. The goal of this article is to summarize the contributions from the existing literature in the AM and Big Data field and prospect how Big Data methods can offer a better future for AM technology. It also introduces recent developments in AM technology combined with the internet of things (IoT), cloud, and cybersecurity. Future directions in AM and Big Data, which include AM data unification, completed AM data-sharing platform, and smart AM production process is pointed out as well.
Vorheriger Artikel Editorial PIAM March 2021
Nächster Artikel Optimization of 3D printing process parameters to minimize surface roughness with hybrid artificial neural network model and particle swarm algorithm

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Metadaten
Titel
Additive manufacturing embraces big data
verfasst von
Kaiming Bi
Dong Lin
Yiliang Liao
Chih-Hang Wu
Pedram Parandoush
Publikationsdatum
16.03.2021
Verlag
Springer International Publishing
Erschienen in
Progress in Additive Manufacturing / Ausgabe 2/2021
Print ISSN: 2363-9512
Elektronische ISSN: 2363-9520
DOI
https://doi.org/10.1007/s40964-021-00172-8

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