SUBSTANTIATION OF METHODS OF COLLECTION AND ANALYSIS OF DIGITAL DATA FOR EVALUATION OF MACHINE AGGREGATE OPERATION IN MICROSOFT OFFICE EXCEL
Abstract
Current research shows that the potential of land and varieties of crops (except GMOs, which are now banned in Europe) has actually been exhausted. Therefore, today the main way to increase the yield is to meet the needs of the plants due to the quality of technological operations. The quality of the technological operation is up to 30% of the future harvest. The quality of each technological operation shapes the overall quality and influences the final result - the quality, quantity and cost of production. A badly executed technological operation cannot be re-performed or offset by a qualitative performance of a subsequent technological operation. Modern information technology methods can significantly simplify and reduce the cost of evaluating the performance of ma-chine aggregates. Crucial in this situation is the tool by which data is obtained for processing, analysis and decision making. It is a technique that was used to obtain information. The result of the calculation obtained in the laboratory must be consistent with the results of the observation of the terms in the production conditions. To do this, we have developed a mathematical model and a computer program "Machine aggregate", whose algorithm is written in Microsoft Office Excel. This program is being field-tested with LCMZ and Elvorty. The basic condition of the calculations should be a reliable database.df The input parameters of the computer program "Machine aggregate" are design parameters of tractors and machines as well as agroclimatic and physical-mechanical conditions of their work. The main output parameters of the program implementation are the results of machine aggregates work such as cost and quality of work. The developed technique allows to perform a deep analysis of the operational-economic and quality indicators of use of ma-chine aggregate in any the natural and climatic conditions for both existing and projected aggregates.
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