Data-Driven Modeling and Coordination of Large Process Structures

  • Dominic Müller
  • Manfred Reichert
  • Joachim Herbst
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4803)


In the engineering domain, the development of complex products (e.g., cars) necessitates the coordination of thousands of (sub-) processes. One of the biggest challenges for process management systems is to support the modeling, monitoring and maintenance of the many interdependencies between these sub-processes. The resulting process structures are large and can be characterized by a strong relationship with the assembly of the product; i.e., the sub-processes to be coordinated can be related to the different product components. So far, sub-process coordination has been mainly accomplished manually, resulting in high efforts and inconsistencies. IT support is required to utilize the information about the product and its structure for deriving, coordinating and maintaining such data-driven process structures. In this paper, we introduce the COREPRO framework for the data-driven modeling of large process structures. The approach reduces modeling efforts significantly and provides mechanisms for maintaining data-driven process structures.


Dynamic Aspect Operational Semantic Object Type Relation Type Process Structure 
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 2007

Authors and Affiliations

  • Dominic Müller
    • 1
    • 2
  • Manfred Reichert
    • 1
  • Joachim Herbst
    • 2
  1. 1.Information Systems Group, University of TwenteThe Netherlands
  2. 2.Dept. GR/EPD, DaimlerChrysler AG, Group Research & Advanced EngineeringGermany

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