A Framework Enabling Data Integration for Virtual Production

  • R. Reinhard
  • T. Meisen
  • T. Beer
  • D. Schilberg
  • S. Jeschke
Conference paper

Abstract

Due to the increasing complexity of modern production processes, the use of tools providing their simulation is getting more and more common. The simulation of a production process in its entirety, depending on the level of detail, often requires the coupling of several, specialised simulation tools. The lack of uniform structures, syntax and semantics among the considered file formats, the special simulation context and the typical accumulation of huge data volumes, complicates the use of established enterprise application integration solutions. Thus, the need for a tailor-made framework for simulation integration purposes arises. The implementation of such a framework is requested to be easy adaptable, so that changes in virtual production circumstances causes only little efforts in the infrastructure, and at the same time taking care about domain specific purposes. This paper presents such a framework.

Keywords:

Information Integration Interconnected Simulations Integration Infrastructure 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    Conrad, S.; Hasselbring, W.; Koschel, A.; Tritsch, R. (2006): Enterprise Application Integration: Foundations-Concepts- Desgin Pattern-Practical Examples (German Original: Enterprise Application Integration: Grundlagen-Konzepte- Entwurfsmuster-Praxisbeispiele.) Spektrum, Heidelberg.Google Scholar
  2. [2]
    Panian, Z. (2005): Supply chain intelligence in ebusiness environment, in ICCOMP'05: Proceedings of the 9th WSEAS International Conference on Computers, (Stevens Point, Wisconsin, USA), World Scientific and Engineering Academy and Society (WSEAS), pp. 1-6.Google Scholar
  3. [3]
    Schmitz, G.; Prahl, U. (2009): Toward a virtual platform for materials processing, in: Journal of the Minerals (JOM), Metals and Materials Society, vol. 61, pp. 19-23.Google Scholar
  4. [4]
    Myerson, J. M. (2002) The Complete Book of Middleware. Auerbach Publications, MA, Boston.CrossRefGoogle Scholar
  5. [5]
    Halevy, A.; Rajaraman, A.; Ordille, J. (2006): Data integration: the teenage years, in VLDB'2006: Proceedings of the 32nd international conference on Very large data bases, VLDB Endowment, pp. 9-16.Google Scholar
  6. [6]
    White, C. (2005): Data Integration: Using ETL, EAI, and EII Tools to Create an Integrated Enterprise, in tech. rep., The Data Warehousing Institute.Google Scholar
  7. [7]
    Chappell, D. (2004): Enterprise Service Bus: Theory in Practice. O'Reilly Media.Google Scholar
  8. [8]
    Schulte, R. W. (2002): Predicts 2003: Enterprise service buses emerge, tech. rep., Gartner.Google Scholar
  9. [9]
    Rademakers, T.; Dirksen, J. (2008): Open-Source ESBs in Action. Manning Publications Co., Greenwich, CTGoogle Scholar
  10. [10]
    Bernstein, P. A.; Haas, L. M. (2008): Information integration in the enterprise, in: Commun. ACM, vol. 51, no. 9, pp. 72-79.CrossRefGoogle Scholar
  11. [11]
    Vassiliadis, P.; Simitsis, A.; Skiadopoulos, S. (2002): "Conceptual modeling for etl processes," in DOLAP '02: Proceedings of the 5th ACM international workshop on Data Warehousing and OLAP, (New York, NY, USA), ACM, pp. 14-21.Google Scholar
  12. [12]
    Kim, W.; Seo, J. (1991): "Classifying schematic and data heterogeneity in multidatabase systems" Computer, vol. 24, no. 12, pp. 12-18.CrossRefGoogle Scholar
  13. [13]
    Goh, C. H. (1997): “Representing and reasoning about semantic conflicts in heterogeneous information systems.” PhD thesis, Massachusetts Institute of Technology, Supervisor- Madnick, Stuart E.Google Scholar
  14. [14]
    Leser, U. (2007): Information Integration: Architectures and Methods for the Integration of distributed and heterogeneous Data Sources (German Original: „Informationsintegration : Architekturen und Methoden zur Integration verteilter und heterogener Datenquellen“). Dpunkt-Verlag, 1st Edition, Heidelberg.Google Scholar
  15. [15]
    Euzenat, J.; Shvaiko, P. (2007): Ontology matching, Springer, Berlin/New YorkMATHGoogle Scholar
  16. [16]
    Giunchiglia, F.; Shvaiko, P.; Yatskevich, M. (2006): "Discovering missing background knowledge in ontology matching" in Proceeding of the 2006 conference on ECAI 2006, (Amsterdam, The Netherlands), IOS Press, pp. 382-386.Google Scholar
  17. [17]
    Rossiter, U. D. E.; Mokrov, O. (2007): “Integration of the Simulation Package SimWeld into FEM-Analysis Applications for the Purpose of Modelling Welding Processes” (German Original: "Integration des Simulationspaketes SimWeld in FEMAnalyseprogramme zur Modellierung von Schweißprozessen"), Sysweld Forum 2007.Google Scholar
  18. [18]
    Laschet, G.; Neises, J.; Steinbach, I. (1998): "Micro-Macrosimulation of casting processes" 4iéeme école d'été de "Modélisation numérique en thermique", vol. C8, pp. 1-42.Google Scholar
  19. [19]
    Laschet, G. (2002): "Homogenization of the thermal properties of transpiration cooled multi-layer plates" Computer Methods in Applied Mechanics and Engineering, vol. 191, no. 41-42, pp. 4535-4554.MATHGoogle Scholar
  20. [20]
    Schilberg, D.; Meisen, T. (2009): "Ontology based semantic interconnection of distributed numerical simulations for virtual production" in Industrial Engineering and Engineering Management, 2009. IE EM '09. 16th International Conference on, pp. 1789 -1793.Google Scholar
  21. [21]
    Schilberg. D. (2010): “Architecture of a Data Integrator for the Continuous Interconnection of Distributed Numerical Simulations” (German Original: „Architektur eines Datenintegrators zur durchgängigen Kopplung von verteilten numerischen Simulationen”), PhD thesis, RWTH Aachen University.Google Scholar
  22. [22]
    Thain, D.; Tannenbaum, T.; Livny, M. (2005): "Distributed Computing in Practice: The Condor Experience" Concurrency and Computation: Practice and Experience, vol. 17, pp. 2-4.Google Scholar
  23. [23]
    Cerfontaine, P.; Beer, T.; Kuhlen, T.; Bischof, C. (2008): "Towards a flexible and distributed simulation platform" in ICCSA '08: Proceedings of the international conference on Computational Science and Its Applications, Part I, (Berlin, Heidelberg) , Springer, pp. 867-882.Google Scholar
  24. [24]
    Hohpe, G.; Woolf, B. (2004): Enterprise Integration Patterns, Addisson-WesleyGoogle Scholar
  25. [25]
    Gruber, T. R. (1993): "A translation approach to portable ontology specifications" Knowledge Acquisition, vol. 5, pp. 199-220.Google Scholar
  26. [26]
    Zienkiewicz, O. C.; Taylor, R. L. (2005): The Finite Element Method. Basis and Fundamentals. Butterworth Heinemann, 6th ed.Google Scholar
  27. [27]
    it-novum GmbH. (2009): Open Source Business Intelligence (A feature overview the free community version and the commercial versions of Jaspersoft, Palo and Pentaho).Google Scholar
  28. [28]
    Schroeder, W.; Martin, K.; Lorensen, B. (2004): The Visualization Toolkit, Third Edition. Kitware Inc.Google Scholar
  29. [29]
    Apel, T.; Düvelmeyer, N. (2003): “Transformation of hexaedral finite element meshes into tetrahedral meshes according to quality criteria," Computing, vol. 71, pp. 293-304.MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • R. Reinhard
    • 1
  • T. Meisen
    • 1
  • T. Beer
    • 2
  • D. Schilberg
    • 1
  • S. Jeschke
    • 1
  1. 1.Institute of Information Management in Mechanical EngineeringRWTH Aachen UniversityAachenGermany
  2. 2.Institute for Scientific ComputingRWTH Aachen UniversityAachenGermany

Personalised recommendations