Virtual Production Intelligence
Breaking up the disharmony of models used in different design domains by providing semantic connectivity and explorative analysis
The Research Area “Virtual Production Intelligence” is the next logical step in the evolutional
process of the Research Area “The Ontology and Design Methodology of Virtual Production Systems”. Based on the integration and visualisation methods developed in the first funding period, systematic analysis, comprising the tasks identification, integration, extraction, analysis and visualisation of production data, lies in the scope of the second funding period. Virtual Production Intelligence (VPI) draws on the successful concepts of Business Intelligence in the fields of data aggregation/ condensation as well as their interpretation and exploitation.The vision of this Research Area is to reduce the plan-value dilemma by facilitating an aggregation and propagation of heterogeneous data generated by processes from real and virtual production environments. Due to the ontology-based semantic enrichment of data researched in the first funding period, information, by means of semantically enriched data, become available. This facilitates the advanced processing and visualisation of such information, which opens up (i) new opportunities of computer-based analysis and exploration for members of business administration, scientists/ engineers or students leading to a (ii) better understanding of the underlying system’s behaviour, as well as (iii) new possibilities of knowledge transfer. Consequently, Research Area B-1 addresses the following main research question:
How can a unified information handling in Virtual Production help close the gap between deterministic and cybernetic models to facilitate computer-based assistance for decision making processes for the optimisation of dedicated production systems?
In order to answer this research question, it is necessary to research, integrate and validate methods and concepts of Computer Science, Mathematics, Mechanical Engineering and Materials Science including data integration and visualisation, knowledge engineering, modelling and numerical simulation. Here, the main objectives are (i) consolidation of the involved design domains and their harmonisation using top-level and domain ontologies, (ii) development of domain-specific data exploration and data mining techniques and (iii) implementation into an interactive visualisation and presentation. The resulting VPI can be used in education and research as well as in industrial applications. It accelerates and simplifies the process of finding cause-effect relations, which can be used to derive formal correlations. The realisation of the VPI is a fundamental contribution to the technology platform on “Integrated Computational Material and Production Engineering” within the CoE. The VPI comprises methods to analyse and explore problems which arise in the field of Production Engineering, like the comparison of different simulated manufacturing processes considering domain-specific quality criteria. This facilitates deeper understanding of the socio-technical system “production” by providing, for example, ontology-based methods for robust tolerance prediction, comprehensive correlation analysis and sensitivity analysis. Consequently, understanding the system’s behaviour helps to improve the underlying system models by model reduction or model refinement. This provides a sound basis for further optimisation of the production system’s outcome. These contributions reduce the efforts needed for planning and real production and thus help to reduce the plan-value dilemma.
Contact
Prof. Dr.-Ing. Daniel Schilberg
Institute of Information Management in mechanical Engineering (IMA) &
Center for Learning and Knowledge Management (ZLW) &
Associated Institute for Management Cybernetics e.V. (IfU)
RWTH Aachen University
Dennewartstr. 27 , D-52068 Aachen
Phone: +49 (0)241 80-91130 Fax: +49 (0)241 80-91122
E-Mail: daniel.schilberg@ima-zlw-ifu.rwth-aachen.de
Coordinator
Prof. Dr. rer. nat. Sabina Jeschke
Institute of Information Management in mechanical Engineering (IMA) &
Center for Learning and Knowledge Management (ZLW) &
Associated Institute for Management Cybernetics e.V. (IfU)
RWTH Aachen University
Dennewartstr. 27 , D-52068 Aachen
Phone: +49 (0)241 80-91110 Fax: +49 (0)241 80-91122
E-Mail: sabina.jeschke@ima-zlw-ifu.rwth-aachen.de
