A bibliometric review on application of machine learning in additive manufacturing and practical justification

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

A bibliometric review on application of machine learning in additive manufacturing and practical justification

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

A bibliometric review on application of machine learning in additive manufacturing and practical justification

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20300 - Mechanical engineering

Projekt

—

Návaznosti

O - Projekt operacniho programu

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Applied Materials Today

ISSN

2352-9407

e-ISSN

2352-9407

Svazek periodika

40

Číslo periodika v rámci svazku

2024

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

19

Strana od-do

"nestrankovano"

Kód UT WoS článku

001290079400001

EID výsledku v databázi Scopus

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