Digital in NRW - Competence for SMEs
- 01.01.2019 to 31.12.2020
- Organizational Unit:
- Chair of Manufacturing Technology, Digital Transformation
- Federal Ministry for Economic Affairs and Energy BMWi
- +49 241 80 24962
- Send Email
The research project "Digital in NRW - Competence for SMEs" deals with digitalization and networking for small and medium-sized enterprises (SMEs) in the NRW region. The WZL of the RWTH Aachen offers concrete free offers for SMEs along the steps of informing, demonstrating, qualifying, designing and implementing. On the basis of an individual consultation, mobile demonstrators and lab tours can be used to examine modern technologies and networking approaches in the research environment of the WZL. In the company itself, problems are jointly identified, potential analyses are carried out and proposals for solutions are conceived and worked out.
In addition, SMEs are supported in first identifying and then building up the necessary competences for digitisation. These are then tested and evaluated in organised practical workshops. The joint implementation of elaborated concepts then takes place in the company both in the form of pilot projects, in which own industry 4.0 projects are implemented, and in the form of transfer projects, in which newly developed systems, products or processes are jointly implemented, which are tailored to the company. The duration of the projects is between 3-9 months. The overarching goal, small and medium-sized enterprises on their way to digitization and networking, is always in the foreground.
The research group Data-Driven Modeling of Manufacturing Processes supports SMEs in the digital networking of production processes and the persistent traceability of components. In doing so, it draws on its broad experience in fineblanking and grinding as well as the knowledge- and data-driven analysis of current process signals. In this way, SMEs can be supported in the implementation of the Industrial Internet of Things in all three pillars of capture, processing and visualization, so that time-consuming and cost-intensive quality inspections are significantly reduced by trained process models.