Semantic Web Technologies for Intelligent Engineering Applications

Marta Sabou, Fajar Ekaputra, Olga Kovalenko Estefania Serral, Thomas Moser, Roland Willmann

Semantic Representation and Integration of Engineering Knowledge (SRI)

Christian Doppler Laboratory Software Engineering Integration for Flexible Automation Systems

Tech

. Int

erop

.Tool Mec.

Tool Elec.

Workflow

Analysis

SCADA

Tool SW

Model Mec.

Model SW

Model Elec.

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Scientific American, May 2001:

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Multi-disciplinary Engineering for Cyber-Physical Production Systems (CPPS)

Hydro Power Plant Use Case: Example Signal Data

Mechanical Engineering Result (OPM Signals)

Electrical Engineering Result (EPL Signals)

Implicit Links

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“All safe software variables should be linked to exactly two sensors”

Software Eng. Mechanical Eng. Electrical Eng.

Intelligent Engineering Applications: Cross-disciplinary Constraint Checking

SELECT ?kks ?signal WHERE { {SELECT ?kks WHERE { ?kks :hasSignal ?signal } GROUP BY ?kks HAVING (COUNT (?signal) >= 2)} ?kks :hasSignal ?signal}}

V_D only linked to one sensor!

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Product Hierarchy

Process Hierarchy Requirements

Resulting Process Plan in Target

Production System

Chocolate Cake Provider

Chocolate Gloss Provider

Chocolate Sponge Dough Provider

Bitter Chocolate Provider

Gloss Provider

Chocolate Cake

Chocolate Sponge Dough

Bitter Chocolate Gloss

Chocolate Gloss

Chocolate Gloss

Provider

Chocolate Cake

Coating Chocolate Gloss

Chocolate Sponge Dough

Chocolate Sponge Dough

Provider

Chocolate Gloss

Bitter Chocolate

Gloss

Bitter Chocolate

Provider

Gloss Provider

provides

requires

Intelligent Engineering Applications: Flexible Matchmaking based Ramp-up Processes

Source: R. Willmann, S. Biffl, E. Serral. Determining qualified production processes for new product ramp-up using semantic web technologies. i-KNOW '14 7

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Common Concepts provide a common vocabulary to speak about the data in common They link distributed and heterogeneous (local) data models.

Data Integration: Common Concepts

Key Result 1: Engineering Knowledge Base (EKB)

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Common Concepts Ontology

AutomationML Ontology

Key Result 1: Engineering Knowledge Base (EKB)

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Problem: Integration of AutomationML Files

①Complex data structure with intricate links between disciplines ② Integration of AutomationML files from different disciplines important ③Limited support for cross-disciplinary analytics ④Limited options for platform independent browsing of AutomationML data

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Enables integration, browsing, querying, and analysis of diverse engineering models represented in AutomationML.

Technology transfer: AutomationML Analyzer

Source: M. Sabou, F. J. Ekaputra, O. Kovalenko, S. Biffl (2016). Supporting the Engineering of Cyber-physical Production Systems with the AutomationML Snalyzer. In 1st Int. Ws. on Cyber-Physical Production Systems (CPPS), IEEE.

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Browsable internal links

Different Views on Data

Tool example: AutomationML Analyzer

Key Result 2: Industrial Validation at Siemens A.G.

Exploratory search powered by Semantic Web-based technologies, to bridge data silos of software architecture knowledge

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Linked Data: May ‘07

> 31 Billion Triples

Media

Geographic

Publications

Web 2.0

eGovernment

Cross-Domain

Life Sciences

Sept. ‘11

Source: http://lod-cloud.net

WEB OF DATA

Linked Data-based Intelligent Applications: Manufacturing Industry

NXP Semiconductors integrates data about 20K products

Source: J. Walker. Is Linked Data the future of data integration in the enterprise? 2013 http://blog.nxp.com/slider-main/is-linked-data-the-future-of-data-integration-in-the-enterprise

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Key Result 3: Towards a “Web of Engineering Data”

Enterprise2 LD

eCl@ss AutomationML

Analyzer (Enterprise1)

Festo

NXP

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ABB

Summary

Semantic Web technologies can effectively integrate heterogeneous data sources

The Engineering Knowledge Base (EKB) provides Semantic Web based methods for data integration

AutomationML Analyzer relies on EKB as part of knowledge transfer to company partner

Semantic Web technologies used as basis for semantic search solutions at Siemens A.G.

Use of Linked Data technologies enables move towards a “Web of Engineering Data”

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