Main contents


Improving industrial competitiveness with condition monitoring

Usability and performance of production plants and dependability of machines and production devices are research themes that have received more and more attention during recent years. The future of condition monitoring brings more extensive use of new technologies such as wireless communication, microsensors and advanced data processing.

This project has the following subprojects: NYKY, ÄKSY, MESTA, LAMA, DADA and PALA, representing different industrial fields. The common factor of all the projects is monitoring and fault diagnosis of systems with advanced methods. The measured quantities differ in the different subprojects, but the algorithms used in signal processing, data mining, data fusion, estimation and prediction are similar. These methods form a basis for automatic fault diagnosis, for advanced condition monitoring and for control as well as for the development of predictive maintenance. The result is a considerable improvement in the competitiveness of the industries applying the methods.

Our research partners are the Institute of Automation and Control (ACI) of the Tampere University of Technology (TUT) and the Finnish Meteorological Institute. Our industrial partners are John Deere Forestry / Plustech, Pyhäsalmi Mine Oy (Inmet Mining Corporation), Outokumpu Technology Minerals Oy, Aspocomp, Space Systems Finland and Vaisala. Our research is financed by Tekes and the industrial partners.


  • NYKY - Application of modern condition monitoring and control concepts in forest machines
  • ÄKSY - Intelligent methods in mining environment
  • MESTA - Model Based Estimation Methods in Analysis of Electronics Manufacturing
  • LAMA - Computational methods in the monitoring of satellite AOCS
  • DADA - Development of data fusion and diagnostics methods in weather station networks
  • PALA - Advanced monitoring of paper quality


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Licentiate Theses

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Master's Theses

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