EXAMINATION OF THE DATA DISTRIBUTION NATURE ON THE CHEMICAL COMPOSITION OF CAST IRON AT THE OUTPUT

Abstract

Introduction. Ensuring the desired chemical composition of cast iron in manufacturing plays a crucial role in determining the quality of metallurgical products and important economic indicators of an enterprise. To achieve this goal, there is a need for the development and implementation of effective forecasting methods that play a key role in the optimal management of the cast iron smelting process to a specified quality. Complex technological processes, such as blast furnace smelting, are influenced by various factors of different natures. These factors affect both the general course and development of the process, as well as its individual properties and quantitative characteristics. Methodology. In the course of the research, the primary focus was on the key aspects of data preprocessing and descriptive statistics methods. The main purpose of descriptive statistics is to provide information about the investigated data in a concise and understandable form. However, before proceeding to describe the available data, it is necessary to analyze their type and distribution, as different types of data require different methods of description and processing. This will also be useful when choosing an appropriate statistical method for hypothesis testing. Scientific Novelty. At present, researchers have not reached a consensus on the distribution law that describes the data on the chemical composition of cast iron at the output. In addition, the author is unaware of scientific publications that thoroughly cover this topic. Hence, there is a need for conducting a study of the stochastic properties of real data on the chemical composition of cast iron in the output of a blast furnace.