Literature DB >> 33809049

Automated Design and Integration of Asset Administration Shells in Components of Industry 4.0.

Jakub Arm1, Tomas Benesl1, Petr Marcon1, Zdenek Bradac1, Tizian Schröder2, Alexander Belyaev2, Thomas Werner2, Vlastimil Braun3, Pavel Kamensky3, Frantisek Zezulka1,4, Christian Diedrich2, Premysl Dohnal1.   

Abstract

One of the central concepts in the principles of Industry 4.0 relates to the methodology for designing and implementing the digital shell of the manufacturing process components. This concept, the Asset Administration Shell (AAS), embodies a systematically formed, standardized data envelope of a concrete component within Industry 4.0. The paper discusses the AAS in terms of its structure, its components, the sub-models that form a substantial part of the shell's content, and its communication protocols (Open Platform Communication-Unified Architecture (OPC UA) and MQTT) or SW interfaces enabling vertical and horizontal communication to involve other components and levels of management systems. Using a case study of a virtual assembly line that integrates AASs into the technological process, the authors present a comprehensive analysis centered on forming AASs for individual components. In the given context, the manual AAS creation mode exploiting framework-based automated generation, which forms the AAS via a configuration wizard, is assessed. Another outcome consists of the activation of a virtual assembly line connected to real AASs, a step that allows us verify the properties of the distributed manufacturing management. Moreover, a discrete event system was modeled for the case study, enabling the effective application of the Industry 4.0 solution.

Entities:  

Keywords:  Asset Administration Shell; Industry 4.0; Internet of Things; MQTT; Manufacturing Execution System; Manufacturing Operation Management; Open Platform Communication—Unified Architecture (OPC-UA); digital twin; industrial Internet of Things

Year:  2021        PMID: 33809049     DOI: 10.3390/s21062004

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  2 in total

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Journal:  Sensors (Basel)       Date:  2022-08-04       Impact factor: 3.847

2.  Open Source IIoT Solution for Gas Waste Monitoring in Smart Factory.

Authors:  Mark Waters; Pawel Waszczuk; Rodney Ayre; Alain Dreze; Don McGlinchey; Babakalli Alkali; Gordon Morison
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  2 in total

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