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Proceedings of CAD'15, 2015, 148-153
New Approach of the Product-specific Knowledge Balance Based on Data Mining of Virtual Prototypes

Stefan Hinsen, Margot Ruschitzka, University of Applied Science Cologne
Peter Gust, University of Wuppertal

Abstract. The development departments of modern companies face big challenges caused by the immensely growing product complexity with its according multidisciplinary Big Data. Not only the big worldwide operating enterprises established innovative technologies of Virtual Prototypes, even small and medium owner-managed companies already meet the challenges of this task and the corresponding Big Data. Several combinations of proprietary engineering and simulation data describe the Virtual Prototypes depending on the industrial sector, the products to be manufactured and the size of the company. The according software tools were historically implemented based on the company’s development and represent in most cases isolated solutions. Besides the explicit knowledge representations, for example wiki software solutions or file-based documentations, the company-specific technology and application know-how is concealed in this Big Data. The technological evaluation of the existing Virtual Prototypes by a comparing survey is impossible. Even if a product data management system had been implemented, it is just possible to use classifications and search for meta data according to the depth of software implementation.

Keywords. Product-specific Knowledge Balance, Technological Capital, Data Mining of Virtual Prototypes, Decision Support

DOI: 10.14733/cadconfP.2015.148-153