Semantic modeling of Big Industrial Data for Predictive Maintenance

Key Takeaways

– Capturing the Meaning of Big Industrial Data
– Industrial Ontologies for Predictive Maintenance (https://www.industrialontologies.org/)
– Ontology Based Software Architectures for Predictive Maintenance

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Speaker Bio

Prof. Dr. Dimitris Kiritsis (Kyritsis) is Faculty Member at the Institute of Mechanical Engineering of the School of Engineering of EPFL, Switzerland, where he is leading a research group on ICT for Sustainable Manufacturing. He serves also as Director of the doctoral Program of EPFL on Robotics, Control and Intelligent Systems (EDRS). His research interests are Closed Loop Lifecycle Management, IoT, Semantic Technologies and Data Analytics for Engineering Applications. He served also as Guest Professor at the IMS Center of the University of Cincinnati, and Invited Professor at the University of Technology of Compiègne, the University of Technology of Belfort-Montbéliard and at ParisTech ENSAM Paris. Prof. Kiritsis is actively involved in EU research programs in the area of Factories of the Future and Enabling ICT for Sustainable Manufacturing. He has more than 220 publications. Since September 2013 Dimitris is Chair of IFIP WG5.7 – Advanced Production Management Systems. From 2013 to 2017 he was member of the Advisory Group of the European Council on Leadership on Enabling Industrial Technologies – AG LEIT-NMBP. He is also founding fellow member of the International Society for Engineering Asset Management (ISEAM), of various international scientific communities in his area of interests including EFFRA and among the initiators of the IOF (Industrial Ontologies Foundry).