Improving Requirement Analysis in Mechanical Engineering through Virtual Prototyping and Interactive Attention Tracking in Virtual Reality
This project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project number 515614446 to research on new techniques to improve the quality of requirement analyses through the use of virtual prototypes and the analysis of attention during the inspection of those prototypes. To this ends, multimodal interaction data, in particular eye-tracking, is gathered and analyzed to improve the prompting procedures and disambiguate verbal reportings on requirements. The project title ReqET is a construct based on Requirements and Eye Tracking.
The project started in Fall 2023 and will continue until 2025. It is a joined project together with partner researchers from Quality- and Processmanagement at University of Kassel under the lead of Prof. Dr.-Ing. Robert Refflinghaus.
Exploration Scenario
Requirements regarding Bicycles
In our exploration scenario, we are using a virtual bicycle company as an example.
Related Work
- L. Stubbemann, R. Refflinghaus, and T. Pfeiffer, “Eye-Tracking zur Kundenanforderungsvalidierung im Produktentwicklungsprozess,” in Qualitätsmanagement in den 20er Jahren – Trends und Perspektiven, Berlin, Heidelberg, 2021, p. 146–165. doi:https://doi.org/10.1007/978-3-662-63243-7_8
- J. Pfeiffer, T. Pfeiffer, M. Meißner, and E. Weiß, “Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments,” Information Systems Research, 2020. doi:10.1287/isre.2019.0907
Team Emden
Responsible Investigators:
Research Assistants:
Ruwim Merling
Project Partners
The team from HS Emden/Leer is primarily responsible for the VR simulation and multimodal interaction analysis technology. Our partners from mechanical engineering at University of Kassel focus on the requirement analysis procedure. Visit the official project website for more information.
This project is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – project number 515614446.