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Abstract

The use of simulation tools in production process planning within industrial environments is already well established. However, this generally involves conducting individual simulations of specific sub-processes using default settings as the boundary parameters. This method does not take into account production history influences on the individual sub-processes. In order to improve planning quality using simulations, the individual simulations need to be linked to form a continuous simulation chain. The methodology for linking simulations described in this paper allows flexible extension of the overall system, allowing incorporation of a variety of heterogeneous simulation chains. In addition to linking distributed simulation resources on an infrastructural level, Internetbased access is also provided, which allows partners to collaborate in setting up simulation chains. There is a data integration component to ensure the correct syntactic, structural and semantic transformation of data between the individual heterogeneous simulations and to ensure all the required simulation data is integrated into a common database. To enable integrative analysis of the simulation data for a whole process, there is an interactive visualisation component which can be used on a variety of visualisation systems, from regular workstation computers through to dedicated virtual reality systems with numerous projection surfaces. Interactive modification of dataset timing within the context of analysis is a key aspect in this respect. In future, the system will be expanded so that interactive analyses can be conducted on the in-tegrated database and bidirectionally coupled with the visualisation component in real time. This will enable intuitive access to the integrated simulation data, even across process boundaries, thus providing optimal support for planning or modification of production processes.

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Correspondence to Thomas Beer , Tobias Meisen , Rudolf Reinhard or Torsten Kuhlen .

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Beer, T. et al. (2013). Platform for integrative simulation. In: Jeschke, S., Isenhardt, I., Hees, F., Henning, K. (eds) Automation, Communication and Cybernetics in Science and Engineering 2011/2012. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33389-7_73

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