Model similarity evidence and interoperability affinity in cloud-ready Industry 4.0 technologies

Pedone, Gianfranco and Mezgár, István (2018) Model similarity evidence and interoperability affinity in cloud-ready Industry 4.0 technologies. COMPUTERS IN INDUSTRY, 100. pp. 278-286. ISSN 0166-3615 10.1016/j.compind.2018.05.003

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Abstract

Cloud computing is revolutionizing IT environments in most fields of economy. Its service-based approach enables collaboration and data exchange on higher level, with better efficiency and parallel decreasing costs. Also manufacturing environments can benefit from cloud technology and better fulfill fast changes in market demands, by applying diverse cloud deployment models and by virtualizing manufacturing processes and assets into services. As cloud becomes the basis of most innovative manufacturing IT systems, its future role in Cyber-physical Production Systems has to be properly investigated, as their interoperability will play a role of vital importance. In this paper, after a brief introduction to cloud criticality and cloud-based manufacturing, the mutual conceptual similarities in modelling distributed industrial services of two of the major standardization frameworks for industrial Internet architectures are presented: the Industrial Internet Reference Architecture (IIRA) and the Reference Architectural Model Industrie (RAMI 4.0). It is also introduced how their integration feasibility finds a strong affinity in specifications of the Open Connectivity Unified Architecture, a service-oriented architecture candidate to the standardization of Industrial Internet of Things based manufacturing platforms. Finally, the preliminary architecture of a prototype Smart Factory is presented as a case study.

Item Type: Article
Uncontrolled Keywords: Cloud computing; Cloud manufacturing; Industry 4.0 interoperability; IIRA; RAMI 4.0; OPC UA;
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Research Laboratory on Engineering & Management Intelligence
SWORD Depositor: MTMT Injector
Depositing User: MTMT Injector
Date Deposited: 03 Jan 2019 12:17
Last Modified: 03 Jan 2019 12:17
URI: http://eprints.sztaki.hu/id/eprint/9515

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