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Industrie 4.0

Data analytics for the fourth industrial revolution, such as proactive service and maintenance of production resources or finding anomalies in production processes.

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Medicine

Data-driven aspects of medicine are explored, such as the need-driven care of patients or IT controlled medical technology.

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Smart Infrastructure

Untersuchung datengetriebener Aspekter städtischen Lebens, bspw. der Verkehrssteuerung, der Müllentsorgung oder der Katastrophenbewältigung, bedarfsgesteuerte Optimierung von Verbrauchsmodellen, basierend auf Daten intelligenter Stromzähler.

Featured Projects

  • SDSC BW: In search of unknown correlations

    Nowadays at Fuchs Schmierstoffe GmbH, a modern production of oils and lubricants is inconceivable without information technology. The resulting data are worth gold: they provide information about the product itself (in the resource planning system – ERP) and about the materials used (in the process control system – PLS). To achieve the desired product quality, it is important to monitor and control the complex process at various points.

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  • SDSC BW: The appropiate algorithms for Big Data

    Every day Echobot Media Technologies GmbH analyzes millions of texts from websites, social media and news sites for its customers. These analyses help, for example, with marketing, sales or the optimization of public relations. In order to analyze digital contents, Echobot first has to perform an automatic classification of the recorded texts.

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  • SDSC-BW: Smart data analyzes reduce maintenance intervals for milling machines

    The Hermle AG develops systems that record the machining center as a central parameter, providing information on the condition of the components. This information is analyzed and evaluated accordingly. This can help prevent downtime and precisely determine the need for maintenance. For a smart data analysis of the Smart Data Solution Center Baden-Württemberg (SDSC-BW) data from several machines were provided for a period of 12 months. The initial analysis focused on classifying the state of the axes of the processing center and thus identifying potentials for automated remote maintenance. The second step involved the evaluation by means of supervised learning methods (for example decision trees). The aim of the SDSC-BW experts was to use the data for the prediction of machine problems (predictive maintenance).

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  • Analytics for a Smart Air Quality Network

    The project “Smart Air Qualitiy Network” (SmartAQnet) is based on a pragmatic, data driven approach since the existing data treasures of mcloud.de are combined for the first time and linked with a networked mobile measurement strategy.

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    Ports as Intelligent Logistics Hubs

    This project is part of the Transforming Transport EU lighthouse project. The TransformingTransport project will demonstrate, in a realistic, measurable, and replicable way the transformative effects that Big Data will have to the mobility and logistics market.

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