Article 4316

Title of the article

IMPROVING THE MODELS OF ANALYZING ECONOMIC
PARAMETERS OF COMPLEX INDUSTRIAL SYSTEMS

Authors

Lapshin Edward Vladimirovich, doctor of technical sciences, professor, sub-department of radio equipment design and production, Penza State University (440026, 40 Krasnaya street, Penza, Russia), elapshin@mail.ru
Korneev Andrey Mastislavovich. candidate of technical sciences, associate professor, sub-department of automated control systems, Lipetsk State Technical University (398600, 30 Moskovskaya street, Lipetsk, Russia), weenrok@mail.ru
Miroshnikova Tamara Vladimirovna, candidate of technical sciences, associate professor, sub-department of applied mathematics and information technology, Lipetsk State Pedagogical University named after P. P. Semenov-Tyan-Shanskiy (398020, 42 Lenin street, Lipetsk, Russia), tomik_art@mail.ru

Index UDK

338.512.669.14

DOI

10.21685/2307-4205-2016-3-4

Abstract

The current method of determining costs based on average product cost accounting and allocation of the full amount of the cost by using the coefficients of the difficulties for groups grades makes it impossible to identify the actual costs for the production of a single product. Therefore, an integrated assessment of the impact of the basic technological parameters on resource consumption. Having matrix production volumes (M), matrix of main technological parameters for all types of products XΣ, you can determine the total consumption of technological parameters and express it through a system of equations. The resulting system of equations to predict resource consumption depending on the basic technological parameters. With the help of this system of equations you can evaluate the possible costs as a function of the basic technological parameters. Matrix (K)Σ is once again is based on basic information on production and costs. Having obtained the generalized matrix coefficients of proportionality, it is possible to predict resource consumption depending on the basic technological parameters. You can on new data matrix ΣK again and compare with the original. Ongoing iterationallows you to get dynamic changes and describe its proportionality coefficients using a time series model. Research using dispersion and regression analyses to identify technological parameters, having a significant impact on the consumption of resources. Presented examples demonstrate the similarity of the results obtained in different ways. Reviewed approaches form a system of mathematical models for the analysis of economic indicators of production.

Key words

mathematical models, the regressive analysis, the dispersive analysis.

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Дата создания: 28.09.2016 15:17
Дата обновления: 29.09.2016 15:29