Our third direction is statistical data analysis for MIS (management information system) which predicts potential problems during the production cycle.

This product consists of a variety of machine learning algorithms and models, where each algorithm and model is specialized for a specific task. When building the system, an analysis of all the necessary business processes of the client is carried out, during which the terms of reference for the development of the system for the needs of the client are formed. Further, to train the mentioned models, large-scale data samples are formed from the client's ERP system in accordance with the understanding of the business processes formed during the analysis stage. Each data sample is processed for the subsequent formation of a dataset suitable for training a particular machine learning model.

As a demonstration of the potential of this product, we have developed a system for our client which predicts the likelihood of defects at the stage of the production cycle, based on the data which is formed by different production departments for each order. Additionally, the system will be able to specify the cause of the discrepancy and will describe the possible defect. The current accuracy of this system is 97%. Thus, in 97% of cases, the system correctly predicts the likelihood of a deviation, specifying the place of occurrence, which allows the company's specialists to take timely preventive measures.

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