Resource planning for risk diversification in the formation of a digital twin enterprise
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Date
2020
Journal Title
Journal ISSN
Volume Title
Publisher
Growing Science
Abstract
Recently, there has been explosive growth in the development of the digital industry concept. One of
the most important elements of this concept is the application of mathematical modeling methods
and data mining to create models of production processes and final products, with the aim of making
decisions under stochastic uncertainty. In this paper, a method of diversifying the investment
portfolio in the formation of a digital twin is proposed, which is aimed at reducing the total risk by
distributing existing assets (resources, investments, etc.) between the analog and digital enterprises.
Three types of scenario are proposed: pessimistic - when an enterprise - a pessimist - does not show
risk exposure under this scenario when forming a digital counterpart; neutral - when an enterprise
shows a neutral attitude to risk (indifference); optimistic - enterprise - optimist is exposed to risk, in
particular the risk of untapped opportunities. The result is a set of optimal portfolios, each reflecting
a particular position of the enterprise on the risks of untapped opportunities and a certain scenario of
forming a portfolio structure, taking into account the relationship between the individual components
of the risks of untapped opportunities. Highlighted the advantages of technology "digital twins" for
business. Digital counterparts use the data obtained from sensors installed on production lines or on
the basis of the final product to predict equipment malfunctions, optimize product quality and reduce
the negative impact of production processes on the environment.
Description
Keywords
Digital twin, Resource planning, Stochastic uncertainty, Risk diversification, Investment portfolio, Digital twin prototypes, Digital twin instances, Digital twin life cycle
Citation
Resource planning for risk diversification in the formation of a digital twin enterprise / A. V. Liezinaa, K. A. Andriushchenko, O. D. Rozhkoc [et al.] // Accounting. –2020. – Vol. 6. – P. 1337–1344.