Abstract
Improving the efficiency of the work of metallurgical enterprises in terms of providing consumer requirements for the indicators of physical and mechanical properties of steel rolling and reducing metal content of constructions, obtained from it, is currently an urgent scientific andtechnical task. Its solution in the conditions of rolling production of ukrainian enterprises is possible due to the processing and analysis of experimental data on technological modes of rolling using Big Data technology, that will improve the quality of finished metal products and their competitiveness in the market. It is determined that the main problem while working with the received big data is lack of a single approved spreadsheet form in MS Excel for further statistics, aswell as manual processing mode, which significantly complicates further data analysis, the rapid development of rolling technology and in some cases reduces the effectiveness of technological decisions. A unified database of factual data has been created, an algorithm for its sequentialreading and verification has been developed, as well as software that in an automated mode allows organizing, analyzing and summarizing the available amount of experimental data that corresponds to real rolling conditions, it is possible to filter out invalid data first and prevent duplicate rows when importing. The regression coefficients for mathematical models that predict values of strength limit, yield limit and relative elongation of plate iron material are determined. The variancebetween the experimental and calculated values of the mechanical properties of thick sheets is estimated. It is concluded that the introduction of software at the enterprise allows to reduce timefor processing and completing customer requests, as well as reducing the number of testing rollings and heat treatment to correct the mechanical properties of the rolling.
Highlights
Підвищення ефективності роботи металургійних підприємств з точки зору забезпечення вимог споживачів щодо показників фізико-механічних властивостей сталевого прокату та зниження металомісткості конструкцій, які з нього отримують, є на даний час актуальною науково-технічною задачею
Перспективним напрямком аналізу великого обсягу структурованих та неструктурованих даних на промисловому підприємстві є використання технології Big Data [1], що дозволяє покращити якість готової продукції та її конкурентоспроможність на ринку, а також підвищити ефективність технологічних рішень [2]
It is determined that the main problem while working with the received big data is lack of a single approved spreadsheet form in MS Excel for further statistics, as well as manual processing mode, which significantly complicates further data analysis, the rapid development of rolling technology and in some cases reduces the effectiveness of technological decisions
Summary
The segmentation of the stationery market, analyzes the demand, the main trends, the prospects for development and the existing problems are considered in the work. Modeling of business processes of the office supply store network was carried out, IDEF0, DFD, IDEF3 diagrams were constructed using the IDEF methodology for the AS-IS variant. The conclusion is that re-engineering requires wholesale business processes related to the evaluation of suppliers, which is currently determined by subjective judgments about their activities of the store director. The main criteria for evaluation of office supply store suppliers are analyzed and their classification is given. Measures to reengineer the modeling of business processes of the office supply stores' shopping network based on the mathematical model are proposed. The conclusion is made about the prospects of re-engineering other wholesale business processes as such, which provides the main revenue for the stationery store
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