Vision Statement

The intended research priorities and teaching activities for the Full Professor of Data-driven Maintenance Management and Research Group of Production and Maintenance Management (PIM) at the TU Wien are essentially focused on enabling, enhancing and sustaining the capability of cost effective, resource efficient, resilient and sustainable production and maintenance management along industrial, circular value-added chain.

In accordance with the mission statement of TU Wien “Technology for People”, the ultimate goals are to contribute to i) developing excellence in scientific research, ii) teaching a comprehensive and future-oriented set of skills, iii) opening up new and equal opportunities to everyone, and iv) raising public awareness.

Contribution to Sustainable Development Goals (SDGs)

  • SDG 4 - Quality Education
  • SDG 8 - Decent work and economic growth
  • SDG 9 - Industry, Innovation and Infrastructure
  • SDG 12 - Responsible consumption and production
  • SDG 13 - Climate action


[Translate to English:] PIM

Research Strategy

Our research strategy is well aligned to the TU Wien’s research focal area on Digital Transformation in Manufacturing and Sustainable Production and Technologies. Further, it contributes to the primary research areas of the Faculty of Mechanical and Industrial Engineering in particular to “Materials, Production and Management” and “Digital Engineering Innovation” and is tailored, but not limited, to the demands of the manufacturing enterprises and asset industry in Austria and neighboring countries.

Our overall goal is to explore, examine and establish future oriented concepts for Data-driven Production and Maintenance Management along the entire value-added chain considering four dimensions and their interactions, namely i) Physical Systems, ii) Cyber Systems, iii) Human and Organization, and iv) Technology including digital technologies and data-driven approaches for optimization and innovation. In particular, design, development, evaluation, validation, transfer and integration of data-driven approaches should contribute into the optimization of industrial systems, processes and products. This life-cyclic approach will enable, enhance and sustain the intelligent capability of manufacturing enterprises and asset industry, especially SMEs, ranging from diverse sectors (e.g. energy, electronics, automotive, transport) to cope with future market demands, societal, demographic and environmental changes towards human-centered, resilient and sustainable industrial ecosystem. 

What do we do?

  • Fundamental research on integrative production and maintenance planning and optimization and asset management enhanced by the scientific trends on cyber physical production systems (CPPS), AI, semantic technology, Natural Language Processing (NLP).
  • Applied-oriented research on data-driven production and maintenance management (predictive/prescriptive/knowledge-based maintenance) and maintenance for sustainability inspired by emerging industrial trends, namely “Twin Transformation”, “Industry 4.0” and “Biological transformation in Manufacturing”.
  • Practice-based research on production and maintenance professions from the angle of learning factories, in particular work-based learning for manufacturing enterprises.

Whom do we work for?

  • Researchers and Scientists in Production and Logistics Management as well as operations and asset management
  • Industrial Data Scientists
  • Maintenance Professionals and Practitioners
  • Learning factory experts and enthusiasts

How do we bring a cooperation into reality?

  • Partnership within research and industrial projects (national, European and international funds)
  • Scientific Advising and supervision (Diploma/Master theses, industry funded projects, etc.)
  • Training and Conferences in cooperation with international and national institutions, namely IFAC, IEEE, CIRP and IALF.