Production management in a market economy, when the numerous risks of an enterprise are sometimes difficult to classify, make it necessary to use various methods and computational programs to make the most accurate and informed decisions. For management to be effective, it is important not only to choose the most rational strategy, but also to select a set of applied tools that will reduce the time and labor costs for solving managerial tasks.

Methods of forecasting and calculating the risk of marriage of finished products

Modern systems of artificial intelligence allow you to automatically predict the quality of products and assess the likelihood of the risk of a marriage. Our team has developed an artificial intelligence system - CING, which continuously analyzes data from sensors and measuring equipment. Through the use of diverse metrics and evaluation of equipment operation trends, the system provides the ability to predict with high accuracy the result of the technological process, to its actual completion, and to make the necessary adjustments automatically to improve the final quality of the product.

Such an analysis becomes possible through the use of modern neural network algorithms of artificial intelligence system CING.

In real-time, the system collects information from various sensors and assesses the quality of the process flow, after which it provides data in the form of information about the expected quality and the likely risk of a finished product.
The use of artificial intelligence in this case improves the awareness of the process, reduces the likelihood of human error, and increases the ability of staff to make timely adjustments to achieve maximum efficiency of the process.

Automated process control is a cost-effective solution for enterprises. The forecasting and calculation of production risks carried out in this way can reduce internal costs, as well as reduce the labor costs of collecting and analyzing all the necessary data. As a result, the company receives a minimum share of manufacturing defects, reduced operating costs, reduced downtime and the number of emergency cases in the absence of continuous monitoring by individual specialists.

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