Hochschule Mittweida University of Applied Sciences is a university of applied sciences in Central Saxony with a strong focus on research and transfer. Founded in 1867 as a technical centre, the state university has more than 6.000 students in five faculties and four research focuses. In the last few years the university has continued to develop its fields of research competences. The decision of the German Rectors' Conference (HRK) to include Mittweida University in the Research Map of the German Rectors' Conference (www.forschungslandkarte.de)) with its four research focuses has been an important factor in this regard: • FSP1: Laser Technologies • FSP2: Product and Process Development • FSP3: Digitalisation in Economy and Society • FSP4: Applied Informatics. We have extensive experience in project coordination and participation, e.g. FORMOBILE: From mobile phones to court – A complete FORensic investigation chain targeting MOBILE devices (H2020, project no. 832800), LaMoFlo: High-rate laser surface texturing of 3D injection molds to fabricate functionalized easy-flow polymeric containers (M-ERA.net call 2019) and NiWRe Alloys: Electroplating NiW and NiRe alloys as functional alternative coatings (M-ERA.net call 2020), and PULSE: High-Power Ultrafast LaSErs using Tapered Double-Clad Fibre (H2020, project no. 824996) as well as ADVENTURE: Advanced coating substrate preparation by shifted and ultrafast laser texturing (M-ERA.net call 2020). Moreover, we are member of the European University Alliance EURECA-PRO. Additionally, we are or have been taking part in further EU programmes like FP7, ECSEL JU, EIP-AGRI, LEADER, ERASMUS+, „Leonardo da Vinci“, EUAsia Pro Eco, or EU Alfa.
We offer a highly practice-oriented, collaborative research and development approach and tailor each collaboration to your individual needs.
Early idea
Expertise offered
Data technologies | Assistance and Expert systems
Data technologies | Design of an adaptable Digital Product Pass:
Enabling technologies | Robotic / handling - and assistance systems
Data technologies | (AI based) Material and Product Design, Decomposition and Separation
Enabling technologies | Industry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains
Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
Data technologies | (AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths
Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)