OMiLAB: A Smart Innovation Environment for Digital Engineers

Karagiannis, Dimitris; Buchmann, Robert Andrei; Boucher, Xavier; Cavalieri, Sergio; Florea, Adrian; Kiritsis, Dimitris; Lee, Moonkun

doi:10.1007/978-3-030-62412-5_23

Cited by 18 publications

(6 citation statements)

References 18 publications

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“…The primary citing article of this cluster is by Mei, P (2020.0-JAN) [73] published in Frontiers in Neurorobotics. The most frequently cited members within this cluster are Human (64), Article (46), and Simulation (40). Cluster #5, the sixth largest, contains 4 members and holds a silhouette value of 0.995.…”

Section: Keyword Analysis Of Digital Twin For Agriculturementioning

confidence: 99%

“…Cluster #2, ranked third in size, encompasses 12 members with a silhouette value of 0.634 and is also labeled as "digital engineer" by LLR. The major citing article within this cluster is on Omilab, a smart innovation environment for digital engineers, authored by Karagiannis, D (2020.0-JAN) [40]. The most cited members within this cluster are from Italy (19), France (13), and Finland (11).…”

Section: Country Collaboration Analysis Of Digital Twin For Educationmentioning

confidence: 99%

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Scientometric Insights of Digital Twins in Industry 4.0

Kaur,

Bhatia

2024

Preprint

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Industry 4.0 is a new era of digitization that integrates digital technologies to create smart, interconnected production systems, marking a paradigm shift in different domains. One of the key technologies in this era is 'Digital Twin', which offers virtual representations of physical assets and processes. It is crucial to analyze the role of digital twin technology in the context of Industry 4.0 using scientometric analysis with citeSpace, a powerful tool for visualizing and analyzing citation networks. This research focuses on the growth trajectory of digital twin literature, identifies influential authors, institutions, and journals, and analyzes the geographical distribution of research contributions from the Scopus database for 2018-2024. The findings reveal insights into the current state of digital twin research, its impact on Industry 4.0, and opportunities for future exploration and collaboration in this rapidly evolving field.

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Section: Keyword Analysis Of Digital Twin For Agriculturementioning

confidence: 99%

Section: Country Collaboration Analysis Of Digital Twin For Educationmentioning

confidence: 99%

Scientometric Insights of Digital Twins in Industry 4.0

Kaur,

Bhatia

2024

Preprint

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“…Rationale A typical enterprise modeling community member, a language designer or business analyst, does not necessarily need to be a programmer, nor does s/he necessarily have a mathematical background, cf. [39,42,73,106,121]. While we strongly encourage language engineers to leverage the power of formal verification in the DSMM design process, we are aware that the application of formal methods may not be necessarily one of the skills that a typical language engineer possesses, and quite often is not part of conceptual modeling courses, cf.…”

Section: Implications For Educationmentioning

confidence: 99%

Validation and verification in domain-specific modeling method engineering: an integrated life-cycle view

Kaczmarek-Heß

Kinderen

2022

Softw Syst Model

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published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User

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“…Experimentation and Validation FeedbackKTC HPI-ULBS has implemented in 2019, thanks to HPI Potsdam and, based on collaboration between OMiLAB NPO, ULBS, industrial cluster PrelMet Transylvania and Continental Sibiu company within DigiFoF 11 ERASMUS+ KA2 project, a research infrastructure12 (Fig.4) as key asset of a digital ecosystem specific to scientific-innovative activities[13]. Multidisciplinary working teams formed by researchers, students, masters and doctoral students from ULBS but also from partner companies collaborate for developing innovative products / services, acquiring new skills like Creation of Business Ecosystems, Smart Modeling and Digital Twin Engineering.…”

mentioning

confidence: 99%

Successful Knowledge Transfer – A Boost for Regional Innovation

Florea

Meinel

2021

IFIP Advances in Information and Communication Technology

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Innovation is the only way the EU can maintain a strong, sustainable and competitive economy. However, at present there are large imbalances between degrees of innovation of EU countries. Statistics of 2018 and 2019 classify Romania as the least innovative country of EU. One solution to mitigate this drawback consists of development of collaborative networks that replicate the best models of innovation from advanced countries and adapt them to underdeveloped countries from Europe. Such a collaborative network was proposed by HPI Potsdam in 2018 to ULBS with the aim to create an active knowledge transfer center between academia and business/society in the Sibiu region. This paper describes how the center contributes to increasing competitiveness in the Sibiu region by creating collaborative networks, digital education and training platforms as well as fostering applied research projects building on HPI's experience in Potsdam, Germany.

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OMiLAB: A Smart Innovation Environment for Digital Engineers

Cited by 18 publications

References 18 publications

Scientometric Insights of Digital Twins in Industry 4.0

Scientometric Insights of Digital Twins in Industry 4.0

Validation and verification in domain-specific modeling method engineering: an integrated life-cycle view

Successful Knowledge Transfer – A Boost for Regional Innovation

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