This project aims at developing a framework, comprising a methodology and supporting tools, for the
systematic and efficient design of Digital Twins providing answers to two question types: (i) production
parameters - product performance correlation and (ii) faults detection and diagnosis. The purpose of the
framework is to support the user in choosing which data sets and models to combine and how to deploy them
(Digital Twin implementation) to get an answer to the posed questions based on application specific
requirements and criteria. The final goal is to use the developed framework to efficiently design Digital Twins
and implement them for seven industrial use cases.