The increasing number of interconnected devices and sensors, the "Internet of Things" (IoT), enables diverse and new applications. However, it also leads to a rapidly growing amount of data. Processing data at its point of origin (Edge Computing) helps to deal with it efficiently. Edge Computing strengthens the functionality, sustainability, reliability, and cost-effectiveness of electronic applications through the use of Artificial Intelligence and networking.
The project develops processors specialized in decentralized, sensor-based data processing for the purpose of process monitoring. Within a complex manufacturing process, such as the production of electronic components, various production conditions can negatively affect quality. By collecting freely available data from the workpiece, such as temperature, operating noise, and magnetic fields, the local environment is recorded very accurately. The data is then condensed, evaluated using AI, and compared to a predetermined optimum. With real-time evaluation, it is possible to react to unequal environmental conditions and different qualities of raw materials during production.


Edge Computing Modules for Resilient Electronics Manufacturing with Adaptive Process Optimization



Duration Time

08/22 - 07/25




Subproject: RISC-V-based AI Accelerator

The RISC-V (Reduced Instruction Set Computing Five) is an open-source instruction set architecture (ISA) that is becoming increasingly important for companies which care about

  • Flexibility and customization
  • Security and authenticy
  • Avoiding vendor lock-in
  • Innovation in open-source technology

Creonic wants to enable its customers making use of this features and makes its existing and future products ready to use alongside with the RISC-V.
Therefore, a joint reasearch project has been introduced, using a Microsemi Polarfire RISC-V with Creonics AI-Architecture, enabling IoT (Internet of Things) and Edge computing in sensitive industry applications for large scale production chains

Project Partners

The project consortium consists of:

 The project is funded by the Federal Ministry of Education and Research 

Learn more about