Chapter

Semantic Web Technologies for Intelligent Engineering Applications

pp 17-51

Date:

Multi-Disciplinary Engineering for Industrie 4.0: Semantic Challenges and Needs

  • Stefan BifflAffiliated withInstitute of Software Technology and Interactive Systems, CDL-Flex, Vienna University of Technology
  • , Arndt LüderAffiliated withOtto-von-Guericke University/IAF
  • , Dietmar WinklerAffiliated withInstitute of Software Technology and Interactive Systems, CDL-Flex, Vienna University of TechnologySBA-Research gGmbH Email author 

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Abstract

This chapter introduces key concepts of the Industrie 4.0 vision, focusing on variability issues in traditional and cyber-physical production systems (CPPS) and their engineering processes . Four usage scenarios illustrate key challenges of system engineers and managers in the transition from traditional to CPPS engineering environments. We derive needs for semantic support from the usage scenarios as a foundation for evaluating solution approaches and discuss Semantic Web capabilities to address the identified multidisciplinary engineering needs. We compare the strengths and limitations of Semantic Web capabilities to alternative solution approaches in practice. Semantic Web technologies seem to be a very good match for addressing the aspects of heterogeneity in engineering due to their capability to integrate data intelligently and flexibly on a large scale. Engineers and managers from engineering domains can use the scenarios to select and adopt appropriate Semantic Web solutions in their own settings.

Keywords

Engineering process Systems engineering Cyber-Physical production systems Semantic Web Data integration