EDGE – Analytics for Smart Diagnostics in Digital Machinery Consept

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The overall objective of this research is to develop technical solutions to provide edge analytics for providing autonomous devices and components with high reliability and availability. The technical methods consist of algorithms for processing raw data, requirements for edge processing elements and support by cloud and operator infrastructure. The edge analytics provides predictability, and hence possibilities for operational optimization, diagnostics and predictive maintenance.

EDGE – Analytics fro Smart Diagnostics in Digital Machinery Consept

Project leader: Professor Kalervo Huhtala, Tampere University
Project leader at the University of Vaasa: Professor Seppo Niemi
Research platform/group at the University of Vaasa: VEBIC / Renewable Energies Reseach Group
Project schedule: 9/2018-10/2020
External funding from: Business Finland and project partners and companies
Total budget: 1,8 MEUR
Contact person at the University of Vaasa: Seppo Niemi
Research partners:Tampereen yliopisto, Åbo Akademi, Vaasan yliopisto
Company partners: Wärtsilä Finland Oy, Fingrid Oyj, Wapice Oy, Solita Oy, Ponsse Oyj, Epec Oy, Sataservice Oy, Silo AI Oy, Top Data Science Oy, Meluta Oy, Kyynel Oy

Project duration
External funding for the University of Vaasa
168 000€
Total budget
1 800 000€
Units and groups
Project actors at the University of Vaasa
Renewable energy
Organisation coordinating the project
Cooperation partners
Funding partners