Within proto_lab, a continuous data pipeline for discrete production/order processing will be developed within MS Azure by the end of 2023. This data pipeline must be expanded to include the collection of time series, primarily from the PDC level but also from the PDA level in 2024. The discrete data and time series serve as the basis for the application of AI algorithms within production scheduling as well as material flow and energy management and thus the further development of proto_lab in phase 3 towards "optimal", sustainable production (years 2023 to 2025).
In order to establish an integrated data pipeline of discrete data and time series within a data warehouse, structural issues along the entire process regarding the data model, mutual dependencies, aggregation levels/areas must be clarified and technically implemented in MS Azure.
The proto_lab was created in 2016 as a cross-faculty project with cooperation partners from industry. The aim was to find efficient solutions for meeting increasingly individualized customer requirements. To this end, a highly flexible IoT production environment was created in which people, machines, logistics and products communicate and cooperate with each other directly and decentrally using smart technology.
Using furniture production as a concrete example, an end-to-end Industry 4.0 process was created that maps the complete, intelligent handling of a customer order, from order receipt with capacity and scheduling, through production and assembly, to delivery of the finished product.
The proto_lab is being continuously developed and will serve as a research platform for the use of AI methods and cloud solutions to optimize production processes in phase 3.
In addition to research activities and the partnership-based transfer of knowledge between the university and companies, the proto_lab also offers application-oriented university teaching to prepare students for the challenges of the 21st century.