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Contact: Maria Maleshkova

Project Status: active


The growing use and popularity of sensors and monitoring devices in the context of production industries has paved the way not only for innovative analysis approaches. The combination of both physical devices and their virtual representation to cyber-physical systems allows new flexible and scalable applications. Especially in industrial manufacturing, situation-based (and therefor predictive) maintenance can effectively prevent or reduce the consequences of threatening downtimes. The project targets the technical foundations, potential business cases and legal requirements of a data-driven maintenance approach. Utilizing semantic data models and web interfaces a integrated infrastructure and a platform are developed. Additionally, prototypical applications for real-time work planning and context depending information access for technicians in the field are introduced.

Involved Persons
Maria Maleshkova, Sebastian Bader


from: 1 März 2016
until: 28 Februar 2019
Funding: BMWi


Heidelberger Druckmaschinen, Trumpf AG, USU Software AG, FastLeanSmart

Research Group

Web Science

Area of Research

Semantic Web Services

Publications Belonging to the Project
 - inproceedings
 - book
 - incollection
 - booklet
 - proceedings
 - phdthesis
 - techreport
 - deliverable
 - manual
 - misc
 - unpublished