and Digital Factory Vorarlberg are conducting joint research in the field of smart factory has announced a research partnership with Digital Factory Vorarlberg GmbH (DFV). The joint activities focus on the topics of smart manufacturing and smart factory. […]

The task of the researchers at Digital Factory Vorarlberg GmbH is, among other things, to develop, test and train various algorithms for production optimization. Here comes the multi-model database CrateDB from for use. The first use case is already a small factory environment for fidget spinners, trendy hand gyroscopes to promote concentration and coordination. Several measuring boxes and controllers collect relevant data from a small production line. This data is transferred in real time to CrateDB, where the evaluation takes place in fractions of a second.

“We are looking forward to working with the Digital Factory to advance the dynamic research and business location of Vorarlberg as an innovation cluster. The cooperation is expected to lead to promising partnerships for future major research projects in the field of promising topics smart manufacturing and Industry 5.0. With our technology and expertise, we want to contribute to the realization of many forward-looking projects,“ says Eva Schönleitner, CEO at for cooperation.

“Among other things, we work here with time series data, i.e. time series data. We have already tried this use case with other solutions before, but in the end CrateDB proved to be the best choice for data acquisition and data evaluation. One of the advantages of the database in this scenario is the ease of setup. In production operations, live data can be processed, analyzed and displayed extremely quickly with the CrateDB. CrateDB is therefore much more powerful and user-friendly in smart manufacturing environments than a conventional relational database management system,“ explained Robert Merz, Research Director of Digital Factory Vorarlberg GmbH.

Important data for production planning

In an already implemented application case, the evaluated data can be used to predict how large the energy demand of the factory will be in different production scenarios. Information like this is extremely important for production planning in modern manufacturing environments. The specialists responsible for production planning and control can view the current results on a dashboard at any time. The precise prediction of resource requirements – such as electricity consumption – makes it possible to produce very flexibly and efficiently both in small batch sizes and in large series and to optimize production processes in order to enable more sustainable production.

In the future, the researchers also want to record and predict other parameters in order to optimize as many factors of a production as possible. The conversion to renewable energy is currently a major topic in the industry, supported by the constant search for savings and options to make production sustainable. Intelligent solutions are required here, for the realization of which contributes its part.

For promising projects, the development of a marketable solution should follow after the research phase. The aim is cooperation projects with other industrial and research partners in order to initiate and promote new developments. Currently, mainly companies from Austria are involved, although there are already plans for internationalization, with a focus on the DACH region.

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