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International projects source: SICRIS

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Researchers (9)
no. Code Name and surname Research area Role Period No. of publications
1.  16394  PhD Mirjam Bajt Leban  Civil engineering  Researcher  2019 - 2021  292 
2.  17966  Janez Gomboc    Technical associate  2019 - 2021  3 
3.  37501  PhD Miha Hren  Civil engineering  Researcher  2019 - 2021  60 
4.  22315  PhD Tadeja Kosec  Chemistry  Head  2019 - 2021  337 
5.  34442  PhD Mateja Košir  Materials science and technology  Researcher  2019 - 2021  71 
6.  17353  Viljem Kuhar    Technical associate  2019 - 2021  320 
7.  08281  PhD Andraž Legat  Civil engineering  Researcher  2019 - 2021  486 
8.  37699  PhD Petra Močnik  Materials science and technology  Researcher  2019 - 2021  36 
9.  20335  PhD Bojan Zajec  Civil engineering  Researcher  2019 - 2021  182 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  1502  Slovenian National Building and Civil Engineering Institute  Ljubljana  5866324000  10,455 
Abstract
Corrosion is the most important materials failure mechanism in industry and annually responsible for the costs amounting approximately to 2 trillion €. In this project, corrosion on-line monitoring and prediction software tools are developed to respond to the needs of raw materials industry. For the project partners, the developed tools enable more than 1 M€ annual savings through the prevention of corrosion failures. For the European raw materials industry in whole, the project may enable saving reaching the magnitude of billions of euros. Thus the project is very important for the competitiveness of European Raw Materials sector. The market potential of the tools lie in all industry sectors facing challenges with materials durability in harsh operation conditions. During the project, the initial business plan will be drafted and further developed though a market analysis. The strategy plan for commercialisation is prepared, including estimation of time-to-market and the protected IPR, considering the steps that will be taken after the project, e.g., licencing. The corrosion on-line monitoring and prediction software tools provide the raw materials sector a footstep towards digitalization. Another giant progress is the link to artificial intelligence (AI); it is here used in the computational modelling, yet remote collection of on-line monitoring data allows later for the hidden causalities in the project conditions (e.g., mineral quality in hydrometallurgy) and the detected corrosion rate to be disclosed with the aid of AI.
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