A bibliometric review on application of machine learning in additive manufacturing and practical justification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27230%2F24%3A10255355" target="_blank" >RIV/61989100:27230/24:10255355 - isvavai.cz</a>
Result on the web
<a href="http://www.webofscience.com/wos/woscc/full-record/WOS:001290079400001" target="_blank" >http://www.webofscience.com/wos/woscc/full-record/WOS:001290079400001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.apmt.2024.102371" target="_blank" >10.1016/j.apmt.2024.102371</a>
Alternative languages
Result language
angličtina
Original language name
A bibliometric review on application of machine learning in additive manufacturing and practical justification
Original language description
This paper delves into the cutting-edge applications of Machine Learning (ML) within modern Additive Manufacturing (AM), employing bibliometric analysis as its methodology. Formulated around three pivotal research questions, the study navigates through the current landscape of the research field. Utilizing data sourced from Web of Science, the paper conducts a comprehensive statistical and visual analysis to unveil underlying patterns within the existing literature. Each category of ML techniques is elucidated alongside its specific applications, providing researchers with a holistic overview of the research terrain and serving as a practical checklist for those seeking to address particular challenges. Culminating in a vision for the Smart Additive Manufacturing Factory (SAMF), the paper envisions seamless integration of reviewed ML techniques. Furthermore, it offers critical insights from a practical standpoint, thereby facilitating shaping future research directions in the field.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20300 - Mechanical engineering
Result continuities
Project
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Continuities
O - Projekt operacniho programu
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Materials Today
ISSN
2352-9407
e-ISSN
2352-9407
Volume of the periodical
40
Issue of the periodical within the volume
2024
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
19
Pages from-to
"nestrankovano"
UT code for WoS article
001290079400001
EID of the result in the Scopus database
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