About SKBM 

The Research Group of Smart and Knowledge-Based Maintenance (SKBM) is part of the research area of Industrial and Systems Engineering at the Institute of Management Science (IMW) of TU Wien. The research group of SKBM is aimed at conducting basic and applied-oriented research towards crossing the gap between basic scientific findings and their practical application in predictive and prescriptive maintenance of production systems and in a wider scope health management of physical assets. The ultimate goal is to promote industrial performance by focusing on maintenance related KPIs.  The research team comprising of senior and junior researchers strives to produce tailor-made innovative solutions that are delivered in close cooperation with industry partners (e.g. from automotive industry, machinery and plant engineering as well as electrical and electronics industry) and research institutions in Austria and across Europe.  The research team of SKBM approaches maintenance not only from management but also from industrial data science perspectives, and utilizes methods of AI, semantic technology, big data analytics and ML to efficiently discover knowledge from heterogeneous data structures and provide informed decision alternatives timely and effectively. This future-oriented knowledge-based maintenance approach results in increasing availability of machineries, reducing maintenance costs, optimizing maintenance (business) processes and assisting maintenance practitioners.

Our Mission: Providing knowledge-based, AI-enhanced, human-centered empowering model for orchestration of digital, analytical methods and technologies towards ensuring maintenance thinking, design and operation in Austrian research community and Industry!

What do we do?     

• Fundamental and basic research on future-oriented maintenance strategies and models inspired by the scientific trends on cyber physical production systems (CPPS), AI, semantic technology, Natural Language Processing (NLP) as well as new learning paradigms and task divisions in human-centered CPPS.     
  

• Applied-oriented research on maintenance analytics (predictive/prescriptive maintenance) and human-oriented maintenance inspired by emerging industrial trends, namely “Digital Transformation”, “Industry 4.0” and “Biological transformation in Manufacturing”.     
  

• Practice-based research on maintenance professions from the angle of lifelong learning (LLL), in particular workplace learning and vocational education and training.   
  

Whom do we serve?     

• Researchers and Scientists in Production and Logistics Management     
  
• Industrial Data Scientists     
  
• Maintenance Professionals and Practitioners     
  
• Curriculum and Job Designers  

How do we serve them?