Semantic Web Technologies for Intelligent Engineering Applications

1. Introduction
Stefan Biffl, Marta Sabou

Part I. Background and Requirements of Industrie 4.0 for Semantic Web Solutions

2. Multi-Disciplinary Engineering for Industrie 4.0: Semantic Challenges and Needs
Stefan Biffl, Arndt Lüder, Dietmar Winkler

3. An Introduction to Semantic Web Technologies
Marta Sabou

Part II. Semantic Web Enabled Data Integration in Multi-disciplinary Engineering

4. The Engineering Knowledge Base Approach
Thomas Moser

5. Semantic Modelling and Acquisition of Engineering Knowledge
Marta Sabou, Olga Kovalenko, Petr Novák

6. Semantic Matching of Engineering Data Structures
Olga Kovalenko, Jérôme Euzenat

7. Knowledge Change Management and Analysis in Engineering
Fajar Juang Ekaputra

Part III. Intelligent Applications for Multi-disciplinary Engineering

8. Semantic Data Integration: Tools and Architectures
Richard Mordinyi, Estefania Serral, Fajar Juang Ekaputra

9. Product Ramp-up for Semiconductor Manufacturing Automated Recommendation of Control System Setup
Roland Willmann, Wolfgang Kastner

10. Ontology-Based Simulation Design and Integration
Radek Šindelář, Petr Novák

Part IV. Related and Emerging Trends in the Use of Semantic Web in Engineering

11. Semantic Web Solutions in Engineering
Marta Sabou, Olga Kovalenko, Fajar Juang Ekaputra, Stefan Biffl

12. Semantic Web Solutions in the Automotive Industry
Tania Tudorache, Luna Alani

13. Leveraging Semantic Web Technologies for Consistency Management in Multi-viewpoint Systems Engineering
Simon Steyskal, Manuel Wimmer

14. Applications of Semantic Web Technologies for the Engineering of Automated ProductionSystems—Three Use Cases
Stefan Feldmann, Konstantin Kernschmidt, Birgit Vogel-Heuser

15. Conclusions and Outlook
Marta Sabou, Stefan Biffl

Avainsanat: Computer Science, Computer Appl. in Administrative Data Processing, Artificial Intelligence (incl. Robotics), Business Information Systems, Industrial and Production Engineering