Laboratory Course: Data Analysis in the Cyber-Physical Brewery (DaBe)
The DaBe laboratory course provides project-based training in the acquisition, processing, and analysis of industrial process data through specific development tasks in a cyber-physical brewery.
Objectives and Content
The aim is to enable students to analyse and further develop industrial production systems using data. To this end, they work in small groups on specific development projects using a real brewing system. At the beginning, they familiarize themselves with existing plant, data, and software structures, use available knowledge resources, and analyse the results of previous projects. Building on this, they independently develop new solution approaches, for example for data acquisition, data processing, analysis, or process optimization. The developed concepts are implemented as prototypes, tested on the system, and documented in a comprehensible manner. The structured maintenance and transfer of project documentation ensures that results can be reused and further developed in subsequent projects.
Core topics
- Project-Based Further Development of Existing Production Systems
- Cyber-Physical Production Systems
- Industrial Data Acquisition and Sensor Technology
- Data-Driven Process Optimization
- Data Processing and Databases
- Use and Further Development of Existing Knowledge Resources
- Industrial Internet of Things
- Fundamentals of Brewing Technology and the Industrial Brewing Process
- Prototypical Implementation, Validation, and Documentation of Data-Driven Solutions
Relevance and Motivation
The further development of digitalized production systems in industrial practice rarely takes place from scratch. New solutions must be integrated into existing equipment, data structures, and software environments and build on existing development stages. The laboratory course reflects this situation in a practical manner. Students learn to systematically familiarize themselves with existing technical systems and documentation, assess available knowledge and previous project results, and develop their own solutions on this basis. In addition to technical competencies in data acquisition, IIoT, and data analysis, the course particularly develops skills in project-oriented work, technical documentation, and sustainable knowledge transfer between successive development projects.
Course Details
- Schedule: Summer semester
- Format: 150 hours, 5 CP, throughout the semester
- Assessment: Oral group presentations (1 interim presentation, 1 final presentation), 60 minutes each
Funding Information
Funded by Stiftung Innovation Hochschullehre.
