Machine Data Processing
We couple the competencies to Data Science for production engineering and develop solutions for the use of data in engineering applications. Our focus is the use of algorithms and their feasible deployment.
In doing so, we pursue a holistic view of machine and technology data "from sensor to visualization and decision". Our focus is on the following areas:
- Machine and process: condition monitoring, anomalies, root cause analysis, interaction models, prognosis, quality assurance, process chains
- Integration of experience, control, measurement and simulation data
- Methods for research data management
- Assists for data automation and guides for methodological handling of data, e.g..
- Holistic methodology for the use of data in engineering applications (DMME Data Mining Methodology for Engineering Applications)
- Paradigm for a usable, domain-specific data-based applications and artificial intelligence (Usable AI) in production
- Procedure for the holistic assurance of data quality
- Mixed modeling of real and synthetic data in greybox models
Offers for companies and research institutions:
- Roadmap development for the introduction of digitalization of laboratory manufacturing and production
- Development of methods for sustainable research data management
- Data exploration for analysis of potential benefits
- Selection of AI algorithms and proof of concept on test bed
Qualification offerings on data-driven methods and algorithms with a focus on applications in production and machine maintenance
Research associates
Current Projects
10/2022 - 12/2024 | ProKI-Dresden - KI in der Umformtechnik |
11/2021 – 10/2026 | PerspektiveArbeit Lausitz – Kompetenzzentrum für die Arbeit der Zukunft in Sachsen und Brandenburg |
02/2021 – 01/2023 | |
08/2020 – 07/2023 | GRK 2250 – Impaktsicherheit von Baukonstruktionen durch mineralisch gebundene Komposite |
07/2019 – 06/2023 | SFB/TR B04 – Exemplarische Parameteridentifikation |