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Automation of asset management – Ukrainian startup Structurescope EG

Improving the realization of the value of organizations’ assets is one of the main tasks of their management. The Life Cycle Asset Management (LCAM) concept and the ISO 55000 ‘Asset management’ standards provide management with the tools to do this, and focus on the technical aspects of the asset life cycle. Critical components (CC) are the most valuable technical assets, 80% of them are made of steel, aluminum and titanium alloys. Almost 90% of their failures are the result of fatigue. Ensuring the fatigue life of explosives is carried out at all stages of their life cycle: construction, materials production, mechanical engineering, and operational. At the construction stage, the requirements for CC and their operational maintenance are established, at the stages of material production and mechanical engineering, compliance with the requirements is monitored, mostly by methods of metallurgical testing (MT). MT takes a lot of time, sometimes more than the main production operation, is poorly automated, requires a large fleet of various equipment and a staff of highly qualified employees from various fields of knowledge.

Our team designed and constructed the Structurescope EG, a digital multi-frequency eddy current non-destructive testing (NDT) system, which can replace 80% of MT methods, reduce the time of checking compliance with structural requirements by ten times and fully automate this process. The principle of the Structurescope EG operation is based on a patented method for determining the structure of the electromagnetic field of a material, which, in its turn, reflects the distribution of its electrons in real space and at different energy levels. The electronic structure of materials is related to the nanostructure of a material by the boundary conditions that are formed due to the geometric factor of the crystal lattice: surfaces/interfaces, edges and vertices, imperfections of the atomic level, such as grain boundaries, dislocations, vacancies and their networks. The complex interaction of the nuclei of atoms and electrons determines all the physicochemical properties of materials, and the interaction of geometric factors at the nanostructure level affects the mechanical characteristics of materials.

Yurii Kalenychenko, Team leader of Structurescope EG, presenting SSEGAI technology at
EIT AI Community Startup Award, Greece, December 2022

Our solution will be useful to innovative businesses seeking to fully automate and digitize their production, in which alloy control operations take place in real time, and a database of digital images of electromagnetic fields of products is created. In metallurgy, this is automated NDT control of the alloys structure, their mechanical and physicochemical properties, in mechanical engineering it is automated NDT of changes in mechanical, physicochemical properties of alloys as a result of their processing by various types of influences: mechanical, thermal, chemical, welding, etc.

Receiving the award from Adrian Bablok, EIT Manufacturing Central GmBH Project Manager,
for SSEGAI for the second place in EIT AI Community Startup Award

In October 2022 our team together with the Virtual Center for Digital Innovation NOSC-UA DIH (Ukraine, Kyiv) team became a winner among the experiments of the DIH-World Innovative Experiment Open Call 2, October, 2022 – April, 2023. The goal of the experiment Structurescope EG + AI (SSEGAI) is to combine the Structurescope EG technology with artificial intelligence (AI) to reduce the time of interpretation of measurements results from 45 to 5 minutes. The implementation of artificial intelligence (AI) in our system will reduce the duration of analysis, which will increase productivity and, as a result, business efficiency. Trained neural networks will be able to quickly find the correct regularities in the composition and structure of materials.

In the course of the experiment Structurescope EG+AI (SSEGAI) our team has completed the whole range of the planned works for the first half of the experiment duration (October, 2022- January, 2023). These works included conducting measurements, developing a mathematical model, selecting an AI type, programming of AI together with development of the SSEGAI user interface, testing of the SSEGAI, and preparation to independent testing of the system in industrial environment. There were more than 400 000 measurements conducted, the data of which were uploaded to the neural network created by us. We have already obtained the 88% correspondence of these data with the determined ductility of the steel in impact tests. In addition, the time taken to interpret data using AI is less than one second, which is significantly better than our target of 5 minutes.

Meeting with Christian Bölling, Managing Director of EIT Manufacturing CLC Central (first to the right from center) and Adrian Bablok, Project Manager EIT Manufacturing Central (second to the right) at EIT Manufacturing Central GmBH office. January 2023.

Today, we are actively conducting communication regarding organization of an independent testing site of the system in real industrial environment. Working meetings were held with representatives of Bavarian innovative community (Bayern Innovative, Fortiss, EIT Manufacturing Central) in January, 2023. Other dissemination plan activities of our team are planned for February and March 2023.

Working meetings were held with representatives of Bavarian innovative community – EIT Manufacturing Central, Fortiss, Bayern Innovative in January, 2023.

Meeting with Maximilian Bock (to the right), Peter Steidl (to the left), Nicolai Harnisch (online) from Bayern Innovative GmbH, Volodymyr Nochvai, NOSC-UA DIH (online). January, 2023

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