Alexis Bernhard

Researcher

Research focus: Software Architecture and Engineering for Automation and Manufacturing

Alexis Bernhard works as a researcher at the interconnected factory chair of DFKI in Kaiserslautern, Germany. Till 2020, he studied Computer Science at the Karlsruhe Institute of Technology in Karlsruhe, Germany and graduated with a master’s degree. In April 2022, he joined the RICAIP project to connect the SmartFactoryKL testbed to the RICAIP network.

For the RICAIP project, Alexis focuses on the topic of Multi-Agent Systems as a framework to send, receive and process external or internal production orders and to coordinate and control all resources of a testbed. One topic in RICAIP is to establish a shared production network between all involved testbeds. His idea to tangle the topic is to develop a Multi-Agent System for the Saarbrücken testbed to enable a shared production scenario. Besides, the Multi-Agent System deals with the tasks of planning and monitoring product orders. Specifically, Alexis plans to implement a system to trace requirements like limiting the energy consumption in the design and to monitor these requirements in the implemented system.

Another focus in RICAIP is to define a data model for the incoming and outgoing data (like orders) of the Multi-Agent System to connect the Multi-Agent Systems in Kaiserslautern and Saarbrücken with the other manufacturing testbeds. For this purpose, he defines an ontology for the production data model, which is currently defined in the Asset Administration Shell Metamodel as a modern Industry 4.0 related standard in Germany.

What do you find the most promising/exciting as a researcher?

For me personally, being a researcher means to be curious about your research topic and to learn and gain in-depth knowledge in that particular topic. This also includes the desire to make the world a little bit better. In my research field of Industry 4.0, this is the desire to revolutionize the modern industry towards a sustainable future by using AI algorithms and techniques.

Would you have any piece of good advice for students?

My advice to students is that you need to set yourself goals, you want to achieve or what you want to do in 5 to 10 years, such as doing research or work in a specific field of work. Then you need to split these goals into manageable subgoals like successfully listening to certain courses. Lastly, but most importantly, you need to continuously work on achieving those subgoals every day as learning for an exam or work as research assistants.