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Data-driven engineering design : a systematic review using scientometric approach
ID
Vlah, Daria
(
Author
),
ID
Kastrin, Andrej
(
Author
),
ID
Povh, Janez
(
Author
),
ID
Vukašinović, Nikola
(
Author
)
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https://www.sciencedirect.com/science/article/pii/S1474034622002324
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Abstract
In the last two decades, data regarding engineering design and product development has increased rapidly. Big data exploration and mining offer numerous opportunities for engineering design; however, owing to the multitude of data sources and formats coupled with the high complexity of the design process, these techniques are yet to be utilised to the best of their full potential. In this study, a comprehensive assessment of the state-of-the-art data-driven engineering design (DDED) in the last 20 years was conducted. A scientometric approach was employed wherein first, a systematic article acquisition procedure was performed, where a dataset of 3339 articles related to engineering design and big data analytics applications were extracted from Web of Science (WoS) and Scopus. Thereafter, this dataset was reduced to a dataset of 366 articles based on concise data screening. The resulting articles were used to analyse the dynamics of research in DDED throughout the last 20 years and to detect the primary research topics related to DDED, the most influential authors, and the papers with the highest impact in the DDED domain. Furthermore, the co-occurrence network of keywords/keyphrases and co-authorship networks were constructed and analysed to reveal the interconnection of the research topics and the collaboration between the most prolific authors. Finally, an insight how big data analytics is being applied through product development activities to support decision-making in engineering design was presented.
Language:
English
Keywords:
data-driven design
,
engineering design
,
product development
,
big data analytics
,
bibliographic analysis
,
network analysis
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FS - Faculty of Mechanical Engineering
MF - Faculty of Medicine
Publication status:
Published
Publication version:
Version of Record
Year:
2022
Number of pages:
19 str.
Numbering:
Vol. 54, art. 101774
PID:
20.500.12556/RUL-142402
UDC:
62
ISSN on article:
1474-0346
DOI:
10.1016/j.aei.2022.101774
COBISS.SI-ID:
128198659
Publication date in RUL:
07.11.2022
Views:
753
Downloads:
156
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Record is a part of a journal
Title:
Advanced engineering informatics : the science of supporting knowledge-intensive activities
Shortened title:
Adv. eng. inf.
Publisher:
Elsevier
ISSN:
1474-0346
COBISS.SI-ID:
7089686
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
podatkovno podprto konstruiranje
,
konstruiranje
,
razvoj izdelka
,
podatkovna analitika
,
bibliografska analiza
,
analiza omrežij
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
P2-0425
Name:
Decentralizirane rešitve za digitalizacijo industrije ter pametnih mest in skupnosti
Funder:
ARRS - Slovenian Research Agency
Project number:
J5-2552
Name:
Napovedovanje sodelovanja med raziskovalci s pomočjo odkrivanja zakonitosti iz literature
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