Increased machine performance using EDGE computing

The project EDGE – Edge Analytics for Smart Diagnostics in Digital Machinery Concept – has performed research on how the performance of machines and industrial installation can be increased using edge computing.

In edge computing, data from sensors is processed locally close to the machine or installation. Edge computing will transfer the computations and analytics insights, typically today done in the cloud, to be available at the machine itself, without delays or the needs for high-speed data connections.

Using edge computing, the overall performance of work machines can be increased considerably, by providing direct feedback to the driver on the current efficiency. This enables the machine to operate efficiently, providing the knowledge and efficiency of the experienced driver for any driver.

For ship engines, edge computing will enable unmanned machine rooms, where the condition and maintenance needs are monitored continuously and without delays. In this way, the efficiency of the engines can be increased, and needed maintenance operations can be scheduled in advance at suitable harbor stops.

The following organizations have been contributing to the two year long EDGE project: Wärtsilä, Wapice, Solita, Silo.AI, Top Data Science, Ponsse,  Fingrid, Meluta, KNL Networks, Epec, and the research organizations Tampere University, Åbo Akademi University, and University of Vaasa. The project has been financed by Business Finland.

The results of the Edge project will be presented in a public seminar, Tuesday February 9, 2021 at 9:30–12:00. Registrations at https://abacus.abo.fi/edge. The seminar is given in English.

For more information

Seppo Niemi, University of Vaasa, 050 430 8519, seppo.niemi(at)univaasa.fi
Kalevi Huhtala, Tampere University, 040 849 0512
, kalevi.huhtala(at)tuni.fi
Jerker Björkqvist, Åbo Akademi University, 050 409 6335, jerker.bjorkqvist(at)abo.fi

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Renewable energy
VEBIC
Technology and Innovations