ZORRO: Engineering for Zero Downtime in Cyber-Physical Systems via Intelligent Diagnostics
Vrije Universiteit Amsterdam, Faculteit der Bètawetenschappen (Faculty of Science) , Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Computer Science, Formal Methods and Tools , Universiteit Twente , Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) , Universiteit Twente , Universiteit Twente, Faculty of Engineering Technology (ET), Applied Mechanics & Data Analysis (AMDA) , Saxion , Vrije Universiteit Amsterdam, Faculteit der Bètawetenschappen (Faculty of Science), Afdeling Informatica (Computer Science), Artificial Intelligence , VU , Vrije Universiteit Amsterdam, Faculteit der Sociale Wetenschappen, Department of Computer Science , Universiteit Twente, Faculty of Engineering Technology (ET), Department of Mechanics of Solids, Surfaces & Systems (MS3) , Universiteit Twente, Faculty of Engineering Technology (ET), Toegepaste Mechanica/werktuigbouwkunde
Start a new DMP in Loading
Vrije Universiteit Amsterdam, Faculteit der Bètawetenschappen (Faculty of Science) , Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Computer Science, Formal Methods and Tools , Universiteit Twente , Universiteit Twente, Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) , Universiteit Twente , Universiteit Twente, Faculty of Engineering Technology (ET), Applied Mechanics & Data Analysis (AMDA) , Saxion , Vrije Universiteit Amsterdam, Faculteit der Bètawetenschappen (Faculty of Science), Afdeling Informatica (Computer Science), Artificial Intelligence , VU , Vrije Universiteit Amsterdam, Faculteit der Sociale Wetenschappen, Department of Computer Science , Universiteit Twente, Faculty of Engineering Technology (ET), Department of Mechanics of Solids, Surfaces & Systems (MS3) , Universiteit Twente, Faculty of Engineering Technology (ET), Toegepaste Mechanica/werktuigbouwkunde
No more system malfunctions? The ZORRO project is working on diagnostic methods for high-tech systems, such as MRI scanners and printers. By continuously monitoring their behaviour with suitable sensors, algorithms from AI can detect anomalous patterns and relate these to their root causes. Suitable measures, such as replacements or repairs, can then prevent failures. We aim at breakthroughs in complexity with ZORRO: not diagnostics for simple components, but for entire systems; efficient monitoring systems that combine different sensor types; automation of diagnostic processes by capturing domain knowledge in diagnostic models and integrate these into the engineering process for high-tech systems.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=nwo_________::5d703d7c9ae85b21ab63b60844adbfba&type=result"></script>');
-->
</script> For further information contact us at helpdesk@openaire.eu