Doctoral College Cyber-Physical Production Systems at TU Wien
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The manufacturing processes of the future need to be highly flexible and dynamic in order to map customer demands, e.g., in large series production or mass customization. Manufacturing companies are not only part of sequential, long-term supply chains, but also of (potentially) extensive manufacturing networks which require agile collaboration between partners. Companies involved in such networks need to be able to design, configure, enact, and monitor a very large number of processes, each representing a different order and supply chain instance. Therefore, the support of complex, scalable, cross-organizational manufacturing processes by according CPPS and software solutions is a foundation for future manufacturing.

One way to achieve this is to port essential concepts from the field of Cloud Computing to manufacturing, to allow agile collaboration through flexible and scalable manufacturing processes:

  1. Leasing and releasing manufacturing assets in an on-demand, utility-like fashion,
  2. Rapid elasticity through scaling leased assets up and down if necessary, and
  3. Pay-per-use through metered service.

Applying these principles, it is possible to move from production-oriented manufacturing processes to service-oriented manufacturing process networks by modelling single manufacturing assets as services in a similar vein as software-as-a-service or platform-as-a-service solutions are already provided by Cloud providers. This principle is known as Cloud manufacturing.

While the theoretical foundations for Cloud manufacturing are manifest, there are still a large number of research questions to be answered. Hence, the main questions to be answered within this PhD subject are:

  1. Approaches to virtualization of Cyber-Physical Production Systems (CPPS) and their integration in business processes using Internet of Things technologies.
  2. Conceptualization and development of a distributed process framework for elastic manufacturing processes, including scheduling and resource allocation mechanisms.
  3. Investigation of Key Performance Indicators (KPIs) and their application in manufacturing process monitoring, process optimization, and failover handling.

PhD-Student and Supervision

PhD-Student: Olena Skarlat, M. Sc., B. Sc., B. Sc.

Olena Skarlat is a PhD student at the Doctoral College Cyber-Physical Production Systems and a project assistant at the Distributed Systems Group of the Institute of Information Systems at TU Vienna.

Her qualifications include a Bachelor’s degree of Computer Science with honors (2008) at the National Technical University of Ukraine "Kyiv Polytechnic Institute", a Bachelor’s degree of Economics and Entrepreneurship / Finance (2008) at the International University of Finances, Kyiv, Ukraine, and a Master’s degree of Information Control Systems and Technologies with honors (2010) at the National University of Kyiv-Mohyla Academy, Kyiv, Ukraine.

Being a researcher at the V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine at the Department of Automated Programming (2010-2014) she was involved in scientific projects on standardization and system interoperability issues, e-services and cloud computing. 


Advisor: Prof. Dr. Schahram Dustdar, Distributed Systems Group (E184-1)

Co-Supervisor: Dr.-Ing. Stefan Schulte, Distributed Systems Group (E184-1)