FORMATION OF INDICATORS OF THE PRODUCTION SYSTEM OF JSC “KVART” FOR THE MACHINE LEARNING MODEL

The study was conducted as part of a cycle of work on the experience of digital transformation of petrochemical production systems. Methodological approaches have been developed for strategic management of digital transformation of production processes using the analysis of technical indicators of a petrochemical enterprise. End-to-end digital technologies are gradually becoming indemand tools in the management of enterprises. One of the most sought-after end-to-end digital technologies is artificial intelligence and machine learning, but the application of these technologies requires high-quality and usable arrays of big data. In this study, the main goal is to form a purified and high-quality data set of technical indicators of the production system of JSC KVART. Correlation and regression analyses of the indicators of the production system of JSC "KVART" were carried out, direct and inverse relationships were revealed, which, when accumulated, will be used as a data set for machine learning for the purpose of predictive production analytics.