linked data for automation systems engineering
TRANSCRIPT
Software Engineering Integration For Flexible Automation Systems
Linked Data in Automation Systems Engineering
Marta Sabou, Fajar J. Ekaputra, Olga Kovalenko, Stefan BifflInstitute of Software Technology and Information System.
Vienna University of Technologyhttp://cdl.ifs.tuwien.ac.at
Christian Doppler Laboratory
Cyber-Physical Systems (CPS)
Flexible, adaptive manufacturing (CPPS) Smart, distributed transportation systems
Software Eng.Mechanical Eng. Electrical Eng.
CPS Engineering Phase
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AutomationML: Industrie4.0 standard
AutomationML consortium: ABB, Daimler, Kuka, Siemens, Volkswagen ….
Open, neutral, XML based, and free industry data representation standard which enables a domain and company spanning transfer of engineering data
Credits: www.automationml.org
Problem Overview
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① Complex data structure with intricate links between disciplines② Integration of AutomationML files from different disciplines important ③ Limited support for cross-disciplinary analytics ④ Limited options for platform independent browsing of AutomationML data
Solution: AutomationML Analyzer
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Relies on Linked Data technologies to enable efficient integration, browsing, querying, and analysis of diverse mechatronic engineering models represented in the AutomationML.
Querying Integrated AutomationML Data
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Predefined SPARQL queries enable monitoring, analysis, validation and defect detection tasks
Take Home Message
Multi-disciplinary engineering (MDE)– Representative for CPS and Industrie4.0– Complex setting
AutomationML– Data exchange format for mechatronic engineering data
Linked Data benefits for MDE:– Ontology-based integration of diverse engineering models– Helping to make implicit connections explicit– Linking to external Web resources (Ecl@ss)– Creation of browser-based visualizations– Query supported analysis of cross-disciplinary data
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