Companies implementing AI in their work can

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of raw materials and components, as well as wholesale buyers of products. The platform allows manufacturers to process a large flow of requests. Currently, 1.5 thousand wholesale orders are placed on it daily, and the number of registered users reaches 350 thousand. The developers managed to optimize the algorithms for classifying requests, which led to a 30% increase in the number of its users and a 10% increase in the number of users returning again, says the founder and CEO of "Supl-biz" Evgeny Dyachenko.

receive support from the ivory coast whatsapp number database Skolkovo Foundation. From 2021 toFederal project "Artificial Intelligence"Grants in the amount of 20 million to 100 million rubles are issued for the pilot implementation of AI projects in industry. The Inkom plant, which produces harnesses for industry, also took advantage of this support. The company received a grant for the implementation of a pilot project to introduce an intelligent adaptive production management system.

The plant's products are used by car assembly plants, manufacturers of household appliances and industrial equipment. Inkom produces more than a thousand product names per month, each line performing 100-200 operations, says Inkom's Director of Finance Marina Kulakova.

Just changing the order of these operations can significantly affect the production time of products. Therefore, it is very important to model the optimal production plan with a minimum number of machine readjustments and taking into account additional factors: changes in technology, problems with the supply of components, malfunction or defect at a certain stage, she explains.

Previously, such graphs were compiled manually by experienced production workers, but it is very difficult for a person to mathematically check all possible options. A neural network easily copes with such a task and allows the equipment to be loaded with standard operations to the maximum.

Thanks to the implementation of the software, it was possible to reduce the time for changeovers by approximately half, which is eight days a month, or 20% additional workload for the enterprise and a corresponding increase in revenue, Marina Kulakova clarifies. "We can already see that this is a promising project," she concludes.