SemProM pp 283-304 | Cite as

Applying Digital Product Memories in Industrial Production

  • Peter Stephan
  • Markus Eich
  • Jörg Neidig
  • Martin Rosjat
  • Roberto Hengst
Chapter
Part of the Cognitive Technologies book series (COGTECH)

Abstract

Industrial production and supply chains face increased demands for mass customization and tightening regulations on the traceability of goods, leading to higher requirements concerning flexibility, adaptability, and transparency of processes. Technologies for the “Internet of Things” such as smart products and semantic representations pave the way for future factories and supply chains to fulfill these challenging market demands. In this chapter a backend-independent approach for information exchange in open-loop production processes based on Digital Product Memories (DPMs) is presented. By storing order-related data directly on the item, relevant lifecycle information is attached to the product itself. In this way, information handover between several stages of the value chain with focus on the manufacturing phase of a product has been realized. In order to report best practices regarding the application of DPM in the domain of industrial production, system prototype implementations focusing on the use case of producing and handling a smart drug case are illustrated.

Keywords

System Prototype Programmable Logic Controller Enterprise Resource Planning Enterprise Resource Planning System Programmable Logic Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Peter Stephan
    • 2
    • 1
  • Markus Eich
    • 3
  • Jörg Neidig
    • 4
  • Martin Rosjat
    • 5
  • Roberto Hengst
    • 5
    • 6
  1. 1.Wittenstein AGIgersheimGermany
  2. 2.DFKI GmbHGerman Research Center for Artificial IntelligenceKaiserslauternGermany
  3. 3.DFKI GmbHGerman Research Center for Artificial IntelligenceBremenGermany
  4. 4.Sector IndustrySiemens AGNurembergGermany
  5. 5.SAP ResearchSAP AGDresdenGermany
  6. 6.BWG Computer Systeme GmbHFreibergGermany

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