Modeling and Connecting Asset Administrative Shells for Mini Factories

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Modeling and Connecting Asset Administrative Shells for Mini Factories
Title:
Modeling and Connecting Asset Administrative Shells for Mini Factories
Journal Title:
Cybernetics and Systems
OA Status:
closed
Keywords:
Publication Date:
26 December 2019
Citation:
Carlos Toro, Alejandro Seif & Humza Akhtar (2020) Modeling and Connecting Asset Administrative Shells for Mini Factories, Cybernetics and Systems, 51:2, 232-245, DOI: 10.1080/01969722.2019.1705554
Abstract:
The supply-chain based (SCB) concept applied to Mini Factories is a very relevant approach for current manufacturing. SBC, allows a network-like interconnectivity between assets by setting up factories inside the premises of the principal manufacturer, allowing more efficient machines utilization. The aforesaid assets need a proper representation and it is there where the core of Industry 4.0 (I4.0) comes to the rescue. According to I4.0, every asset (e.g. a machine, software, sensor or actuator, etc.), should be modeled via an Asset Administrative Shell (AAS). AAS is a knowledge structure that provides a description of the asset, its technical functionality and its relationships to other assets. It can be viewed as the as the data model from where the digital twin stems from. In this paper we extend our previously presented methodology meant for creating Asset Administrative Shells in Mini Factories with a focus on connectivity. By using our proposed methodology, Model Factory @ARTC has been able to quickly connect and integrate diverse assets into our factory of the future, demonstrating some of the enhanced capabilities of Industry 4.0.
License type:
PublisherCopyrights
Funding Info:
This research is supported by the Agency for Science, Technology and Research (A*STAR) under its Advanced Manufacturing & Engineering (AME) Industry Alignment Funding – Pre-positioning funding scheme (Project No: A1723a0035)
Description:
This is an Accepted Manuscript of an article published by Taylor & Francis in Cybernetics and Systems on 26 December 2019, available online: http://www.tandfonline.com/10.1080/01969722.2019.1705554
ISSN:
0196-9722
1087-6553
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