The largest manufacturer of glass containers in the Russian Federation "Sibsteklo" for ₽33 million created a digital double of the plant and increased productivity by 10%
Customers: Siberian Glass (Sibsteklo)
Project date: 2024/12
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The Siberian Glass enterprise (Sibsteklo), the largest manufacturer and recycler of glass containers in the Asian part of Russia, has introduced the technology of "digital twin" production, which made it possible to increase the plant's productivity by 10%. This became known in December 2024. The total investment in the project amounted to ₽33 million, of which ₽20 million is a preferential loan of the regional Industrial Development Fund at 1% per annum with a five-year bank guarantee.
According to TASS, the general director of the plant, Anton More, stressed the importance of import-substituting solutions to reduce the dependence of the glass industry on foreign supplies and ensure growing demand for glass containers.
The software and hardware complex developed in Novosibirsk uses artificial intelligence and vision tools to collect and optimize production indicators, as well as promptly inform about the state of technological processes.
The company employs more than 600 employees, and the geography of supplies covers the regions of Russia from the Urals to the Far East, including Kyrgyzstan, Kazakhstan and Mongolia. Sibsteclo is the only manufacturer of brown and green container glass in the Asian part of the country.
The company's market share in the regions of the Siberian and Far Eastern federal districts reached 75%. The introduction of digital technologies is aimed at increasing the number of affordable products, increasing the speed and efficiency of equipment operation.
The project is being implemented with the support of the Industry Development Fund of the Novosibirsk Region as part of a program to modernize production facilities and introduce modern digital solutions in industry.
The new system allows you to optimize production processes, reduce downtime and improve the quality of products by continuously monitoring and analyzing data in real time.[1]