https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Electric drives as fog nodes in a fog computing-based industrial use case
Tech Univ Denmark, DTU Compute, Kongens Lyngby, Denmark..
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Tech Univ Denmark, DTU Compute, Kongens Lyngby, Denmark..
Tech Univ Denmark, DTU Compute, Kongens Lyngby, Denmark..
2021 (English)In: The Journal of Engineering, E-ISSN 2051-3305, Vol. 2021, no 12, p. 745-761Article in journal (Refereed) Published
Abstract [en]

Electric drives, which are a main component in industrial applications, control electric motors and record vital information about their respective industrial processes. The development of electric drives as Fog nodes within a fog computing platform (FCP) leads to new abilities such as programmability, analytics, and connectivity, increasing their value. In this study, the FORA FCP reference architecture is used to implement electric drives as Fog nodes, which is called "fogification". The fogified drive architecture and its components are designed using Architecture Analysis and Design Language (AADL). The design process was driven by the high-level requirements that the authors elicited. Both the fogified drive architecture and the current drive architecture are used to implement a self baggage drop system in which electric drives are the key components. The fog-based design was then evaluated using several key performance indicators (KPIs), which reveal its advantages over the current drive architecture. The evaluation results show that safety-related isolation is enabled with only 9% overhead on the total Fog node utilization, control applications are virtualized with zero input-output jitter, the hardware cost is reduced by 44%, and machine learning at the edge is performed without interrupting the main drive functionalities and with an average 85% accuracy. The conclusion is that the fog-based design can successfully implement the required electric drive functionalities and can also enable innovative uses needed for realizing the vision of Industry 4.0.

Place, publisher, year, edition, pages
WILEY , 2021. Vol. 2021, no 12, p. 745-761
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:mdh:diva-55820DOI: 10.1049/tje2.12069ISI: 000686554800001OAI: oai:DiVA.org:mdh-55820DiVA, id: diva2:1592639
Available from: 2021-09-09 Created: 2021-09-09 Last updated: 2024-04-05Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records

Desai, Nitin

Search in DiVA

By author/editor
Desai, Nitin
By organisation
Embedded Systems
In the same journal
The Journal of Engineering
Embedded Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 149 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf