Project 17030

DayTiMe

Digital Lifecycle Twins for predictive maintenance

The concept of digital twin can provide solutions for the challenges faced in Smart Manufacturing, e.g. for Predictive Maintenance (PdM) techniques. Even though predictive maintenance and digital twins expected to have a high impact on future smart manufacturing and engineering, there are still very few functioning examples of digital twins being used for predictive maintenance in actual industrial practice. It is the gap DayTiMe is about to fill, integrating findings and solutions from 14 industrial use cases and using a generic value chain model.

Project information

Project name
17030 DayTiMe
Status
Labelled
Call
ITEA 3 Call 4
Challenge
Smart industry
Website
Partners
44
Costs
29,131 k€
Effort
247.76 PY
Countries
Belgium
Canada
Finland
Germany
Netherlands
Norway
Spain
Turkey
United Kingdom

Project partners

Project leader

Name
Friedrich Andreas Halstenberg
Organisation
Fraunhofer Institute for Production Systems and D
Country
Germany
Project involvement
17030 DayTiMe