Artificial intelligence has increased the efficiency of flexible packaging production at Danaflex

2024: Optimizing Flexible Packaging Production

Danaflex-Nano and Innopolis University have completed a project to introduce a predictive analytics digital platform based on artificial intelligence technologies for the production of flexible packaging. The service optimizes the communication of the commercial service with the company's partners by increasing the accuracy of order implementation planning by 10 percent. The operation of the platform can be compared with the functionality of the tandem of foreign AirFlow + products Spark. This was announced on February 13, 2024 by representatives of the RFRIT.

As reported, a large range of ready-made analytics makes it possible to reduce the burden on employees and optimize their working hours. For example, the procedure for creating a sales plan for a year was reduced six times: from 3 months to 2 weeks, taking into account all adjustments and stages of approval. The introduction of a predictive analytics digital platform based on AI technologies eliminates the possibility of error due to the human factor, and means making customer communication even more professional.

neuronets "Danaflex-Nano" has been used in training data over the past few years. The platform takes into account many indicators: process parameters, customer order history, macroeconomic indicators, seasonality, etc. Continuous analysis of a large array of output data gives up-to-date forecasts that determine the operation of production. Artificial intelligence allows you to manage stocks of raw materials and optimize their turnover, optimize the load of production equipment and increase the effective operating time by tens of percent.

The introduction of a digital platform in the company "Danaflex-Nano" was carried out with the grant support of RFRIT within the framework of the national project "Digital Economy." The total cost of the project amounted to 172.3 million rubles, the amount of the grant - 121.5 million rubles.

{{quote 'author
= told Usman Dzhantemirov, Director of Information Technology, Danaflex-Nano|Grant RFRIT played a key role in the implementation of the project to automate business processes through the introduction of algorithms artificial intelligence. It is problematic for the company to independently take on such a financial burden. Grant funding was used for salaries and equipment of workplaces of employees involved in the project implementation, as well as for payment of services of the copyright holder and software integrator - Innopolis University.}}

The flexible packaging business is deeply integrated into the technology chain of food and non-food manufacturers. Therefore, the regular supply of packaging to conveyor belts of the largest enterprises of the country, and therefore the production of their products for the population, depends on the efficiency and stability of the company.

Our company operates in a highly competitive market for flexible packaging and polymer film materials. Various economic and political factors lead to sharp fluctuations in demand, which negatively affects business performance. At the same time, such demand volatility gives the company additional growth opportunities, if such fluctuations are not a surprise. Developed in conjunction with Innopolis University, the AI-based predictive analytics platform helps forecast packaging demand based on historical consumption and production data as well as major market markers. noted Victor Molokin, Director of Business Development and Support at Danaflex-Nano

The project turned out to be voluminous and interesting. The developed platform contains a chain of eight related analytical services. At the beginning of the chain is a service for predicting the probability of an order and its composition, and the final group hosts equipment load planning services. These services and the developed system are involved in all production stages of Danaflex-Nano and help to solve three key business problems: forecasting demand and supply, optimizing production plans and increasing order margins. stated Evgenia Romanova, project manager of the Laboratory for Product Development in the Field of Artificial Intelligence industries University in Innopolis