The Department of Industrial Engineering brings together expertise in the fields of manufacturing, automation, robotics, renewable energy technologies and entrepreneurial engineering models.
From left to right: 3D printing at the Digital Factory, Energieforschungspark Lichtenegg; Digital Factory at UAS Technikum Wien; ‘Robbie’, the service robot for exploration and rescue missions
Head of Department
The ‘Digital Manufacturing, Automation and Robotics’ competence center is concerned with research into intelligent as well as networked methods and approaches that are used to implement flexible production systems. Various robot systems as well as proprietary interfaces for automation technology components are investigated for the purposes of integrating multi-vendor systems while industrial robots are equipped with sensors and tools with the aim of implementing these approaches in practice. Methods for implementing autonomous navigation and the localization of mobile and service-robot systems are developed to this end.
Research is also being carried out into approaches for using collaborative robots in work spaces shared by humans and robots.
The Digital Factory of the UAS Technikum Wien
The development of interfaces for carrying out machining (e.g. milling, deburring, cutting, grinding, polishing) with the help of robots as well as methods for optimizing processes and materials within generative manufacturing sequences are also part of the work that is carried out within this competence center. The Digital Factory at UAS Technikum Wien provides an ideal infrastructure for investigating and developing these subjects.
The courses offered by the ‘Digital Manufacturing and Robotics’ competence center teach the application of CAx technologies as well as material and manufacturing engineering that are used in the manufacturing of products. Knowledge concerning the use of such modern manufacturing methods as generative manufacturing technologies, among other things, is conveyed to this end.
Students in the field of robotics are familiarized with practical aspects of working with industrial robots – the transfer of know-how in the use of simulation tools as well as the implementation of robot applications. Students are taught the methods of calculation used in the development and design of industrial robots and how to use data-based process modeling. This knowledge can then later be used in process optimization, on the one hand, and mobile robotics, on the other. The focus is on statistical methods of data processing and the modeling of processes, which can only be controlled with the help of probabilistic modeling because of the great interference that these processes generate.
An interdisciplinary team of experts in the ‘Renewable Energy Systems’ competence center is concerned at different levels with technological, systemic, ecological and social issues in the field of renewable energy. The experts within this competence center work closely with university and non-university research institutions and collaborate with the energy industry and companies based in Austria. Moreover, they are involved with and have assumed leading positions in more than 30 national and European research projects and training and further education projects. This competence center has taken on leading roles in national and international expert networks, such as the deputy management of the Photovoltaics Research Program by the International Energy Agency (IEA), as well as the scientific management and co-organization of various specialist conferences.
UAS Technikum Wien’s team for small wind turbines at Energieforschungspark Lichtenegg © Ian Ehm/FEEI
- Sustainable and livable buildings and energy-flexible accommodation
- User-oriented, integrated energy systems and technologies, e.g. building-integrated photovoltaics (BIPV), (building-mounted) small wind turbines, grid and system-based electricity storage systems
- Environment and society
- Integrative planning, modeling and simulation, implementation, monitoring, optimization and holistic, interdisciplinary assessment of technologies and systems
- User and stakeholder involvement, co-creation and participation processes, business model development
- Environmental and sustainability assessments, life-cycle analyses and environmental technology assessments
- Experimental design for reliability and accelerated aging
- Data analysis, evaluation and interpretation, road mapping
- Various aspects of measuring and testing work at the Digital Energy Lab and at Energieforschungspark Lichtenegg (Lichtenegg Energy Research Park)
In its teaching and research activities, the ‘Materials Science and Mechanical Systems’ competence center covers the automation of technical and non-technical systems as well as the implementation of intelligent sensor technology for autonomous systems.
Automation technology comprises the sub-areas of metrology, control and feedback control engineering as well as actuator and network engineering.
- Metrology: Methods and procedures for capturing non-electrical quantities as well as methods for adaptation, calibration, evaluation and data interpretation
- Control engineering: Design and optimization of sequence and logic-control systems, programmable logic controllers and associated visualizations
- Feedback control engineering: Methods for the identification of SISO and MIMO controlled systems in the fields of mechanical engineering, mechatronics and process engineering; design and optimization of controllers for applications in mechanical engineering, mechatronics and process engineering
- Actuator engineering: Pneumatic, hydraulic and mechatronic actuators and the optimization of their energy consumptions
- Network engineering: Real-time networking of sensors, actuators, control and feedback control equipment and visualization units
The intelligent sensor technology for autonomous systems is particularly concerned with sensors for the capturing of system statuses and 2D/3D environmental information (indoor/outdoor). The focus here is on the acquisition of relevant physical quantities, signal adaptation, sensor calibration and sensor-data evaluation/interpretation.
The automation technology laboratory at UAS Technikum Wien
- Metrology, control and feedback control engineering and actuators for automation applications
- Real-time networking of sensors, actuators, control and feedback control systems
- Safety – operational safety for automation and robotics
- Mechatronic systems in automation technology
- Intelligent sensor technologies for autonomous systems
The ‘Virtual Technologies and Sensor Systems’ competence center is concerned with the analysis of technological as well as business challenges within the scope of the processes of change resulting from digitalization.
Virtual systems engineering provides a holistic view of change – from product orientation through to service orientation and the associated virtualization of the engineering processes they require.
Combinations of robotics, IoT and augmented reality open up new possibilities in machine-human communication
The expertise ranges from mechanics and machine elements as the basis for modeling and simulating mechanical/mechatronic systems to such virtual technology applications as augmented/virtual reality in industry and entrepreneurial engineering models along with the associated technology-transfer processes. Within this interdisciplinary orientation, the competence center investigates the following questions, among others:
- What benefits are to be gained for business through the use of virtual engineering processes?
- What technologies can be used to generate added value for production systems through networking and mixed-reality applications?
- What are the technical and economic limits for modeling, simulation and the AR/VR representation of mechanical/mechatronic systems?
- How can systems engineering be used within a business context and what basic entrepreneurial attitude is required at the company?
- What demands are being placed on companies and employees by new business models that are being made possible by the successful introduction of new technologies?
- How can new technologies be transferred successfully into established production systems?