Diagnosing for printer maintenance with AI
When exactly does a building or item of equipment require maintenance? Carrying out too much preventive maintenance can be costly. But if you leave it too long, the expense of an emergency repair can be much greater. And we all know that machines have a habit of breaking down at exactly the wrong time. So predictive maintenance is high on the list of priorities of the manufacturing industry. Here, too, artificial intelligence (AI) can make all the difference.
A customer is itching to receive the printed matter he has ordered. The printers are running flat out – as are all the other machines. It is not just tough quality requirements that the graphic industry has to meet, but in many cases tight deadlines as well.
That makes it an ideal sector for introducing predictive maintenance based on artificial intelligence. And that is exactly what TNO and Canon Production Printing (formerly Océ) are currently aiming to do. Together, they are carrying out research into an AI system that stands out in terms of reliable diagnoses and prognoses for professional printers.
AI that understands printers
A lot of different data is needed to be able to estimate the condition of a machine or machine components. But much of that data is incomplete or unreliable. To be able to extract the right conclusions from this mix of data, you need AI that is entirely at home in the world of printers.
This calls for 'hybrid AI' – a combination of data-learning AI and domain knowledge. The AI system is able to modify the likelihood of causal links in the domain model on the basis of a machine’s user data. It can also work out what problems could occur and in what kind of time frame.
Still essential: human expertise
And what about people? The part they play should not be underestimated. Machine learning, then, is just one part of the story. It is precisely the combination of artificial intelligence and human expertise that make this solution so powerful. The big challenge here is to develop an AI system that is capable of accurately combining the input from people and machines alike.
Contact us
-
Jos Hegge
Function not known-
Standplaats:Eindhoven - High Tech Campus 25
-
Telefoon:+3161112206
-
Email:Email Jos
-
LinkedIn:Jos on LinkedIn
-
-
Christopher Brewster
Functie:Senior Scientist at TNO and Professor at Maastricht University on Application of Semantic TechnologiesChristopher Brewster is a Senior Scientist in the Data Science group and Professor of the Application of Emerging Technologies in the Institute of Data Science, Maastricht University. His research has focussed on the application of Semantic Technologies, Open and Linked Data, interoperability architectures and Data Governance, mostly to the food and agriculture domains.
-
Standplaats:Soesterberg
-
Telefoon:+31 6 27 05 46 46
-
Email:Email Christopher
-
LinkedIn:Christopher on LinkedIn
-
-
Daniël Worm
Functie:Senior consultantDaniël Worm is senior consultant at the Applied Cryptography & Quantum Algorithms department, specialized in Privacy Enhancing Technologies like Secure Multi-Party Computation and Federated Learning.
-
Standplaats:Den Haag - New Babylon
-
Telefoon:+31 6 21 13 45 84
-
Email:Email Daniël
-
LinkedIn:Daniël on LinkedIn
-
-
Frank Benders
Functie:Principal Systems Engineer / Architect-
Standplaats:Helmond
-
Telefoon:+31 6 22 48 74 93
-
Email:Email Frank
-
-
Frans van Ette
Functie:Programma Directeur AI-
Standplaats:Den Haag - New Babylon
-
Telefoon:+31 88 866 14 29
-
Email:Email Frans
-
-
Gu van Rhijn
Function not known-
Standplaats:Leiden - Sylviusweg
-
Telefoon:+31 88 866 53 05
-
Email:Email Gu
-
-
Jack Verhoosel
Functie:Senior Consulting Scientist-
Standplaats:Soesterberg
-
Telefoon:+31 6 51 89 46 32
-
Email:Email Jack
-
LinkedIn:Jack on LinkedIn
-
-
Jan-Pieter Paardekooper
Functie:Scientist Integrator-
Standplaats:Helmond
-
Telefoon:+31 88 866 73 15
-
Email:Email Jan-Pieter
-
-
Jasper van der Waa
Functie:Scientist Human-AI CollaborationFor humans and AI applications to function effectively and responsibly, they need to collaborate. My research revolves around shaping that human-AI collaboration.
-
Standplaats:Soesterberg
-
Telefoon:+31 6 11 53 98 95
-
Email:Email Jasper
-
LinkedIn:Jasper on LinkedIn
-
-
Jok Tang
Functie:Research Manager Build EnvironmentHi, I'm Jok, working for the Data Science Department, specialized in (1) explainable and trustworthy AI, (2) hybrid AI where we combine data-driven and knowledge-driven models, and (3) learning from human linguistics.
-
Standplaats:Den Haag - New Babylon
-
Telefoon:+31 6 21 33 27 63
-
Email:Email Jok
-
LinkedIn:Jok on LinkedIn
-
Get inspired
Arnon Grunberg on AI, creativity and morality
Peter Werkhoven, chief scientific officer at TNO, talks to Arnon Grunberg from his base in New York. Grunberg made his breakthrough in 1994 with his novel, Blue Mondays. He has since become one of the Netherlands’ best-known authors. The two talked about AI over dinner some years ago. Today, they finally get the chance to continue their conversation. What is Grunberg’s view on creativity? Can it be taught to machines? And how do humans morally relate to machines?
Responsible decision-making between people and machines
Bias in facial recognition and accidents with self-driving cars. AI must be developed further. The fastest way to do this is in close cooperation with people.
Robotics and autonomous agents
Robotics brings a future-proof industry a big step closer. For example, we are working on automatic path planning with AI techniques.
Knowledge representation and reasoning
Correct and unambiguous information is needed when making a decision. That is why we use AI technology called "knowledge representation & reasoning".
Natural language processing
What is natural language processing (NLP) and how do we use it intelligently? Find out how we use this AI technique to gather information from textual data.