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DIGITAL TWINS OR DIGITAL SHADOWS?

Digital twins are a topic close to the real needs of the market. The issue how to overcome the barrier of transition from development of this technology to its practical application was discussed at the session “Industrial production. Digital twin in the Internet of things ecosystem".

The digital twin allows you to aggregate huge amounts of information, create models and make forecasts. However, when introducing technology, enterprises face a number of problems: the complexity of determining KPI, the lack of personnel in the company that can manage processes after implementation, and also the difficulties associated with collecting data based on outdated infrastructure.

“The length of the port of Antwerp is 120 kilometers. We have created a whole digital nervous system - sensors, drones, unmanned vessels. And the digital twin is a window into this nervous system”, said Erwin Verstralen, director of digital and innovative technologies at the Port of Antwerp.

Enterprises have learned to collect and analyze big data, but their volume is already becoming critical. Alexey Borovkov, the Vice-Rector for Advanced Projects at SPbPU, Head of the STI Center for New Production Technologies, considers “junk” data to be the main problem.

“We collect millions of terabytes of useless data. We spare it and as a result we begin to be over our head in them. But our task is to accumulate more meaningful information. We need a matrix of targets and constraints. Then the digital twin will be able to instantly give an answer to what will happen to the system when the indicators change. In our country, 90% are not twins, but digital shadows. They are not able to give necessary forecasts. For example, Fukushima: they could calculate the tsunami and also the work of nuclear power plant. But they couldn’t combine them, therefore the explosion took place”, said Alexey Borovkov.

The head of the Skoltech Competence Center Dmitry Lakontsev agreed that the law “the more the better” does not work with regard to data: “If you upload nonsense to the network, the network will learn nonsense. 70% of our work is selection and preparation”.

JBMC's Joe Barkai believes that junk data is not a deterrent to technology development, and the value of the Internet of things comes from the ecosystem. This idea was supported by Evgeny Charkin, director of information technologies of Russian Railways JSC: “With the help of blockchain technologies, we combine Russian Railways, manufacturers and service companies. All ecosystem participants have the same data. This greatly optimizes the process. Value is not created only by us or only by the manufacturer, it appears in the ecosystem”.

The panelists agreed that the key challenges are not technology related. It is necessary to change the thinking of people and the organizational structure of enterprises.