Issue |
EPJ Web Conf.
Volume 248, 2021
V International Conference “Modeling of Nonlinear Processes and Systems“ (MNPS-2020)
|
|
---|---|---|
Article Number | 04015 | |
Number of page(s) | 5 | |
Section | Workshop on Advanced Materials Processing and Smart Manufacturing | |
DOI | https://doi.org/10.1051/epjconf/202124804015 | |
Published online | 26 April 2021 |
https://doi.org/10.1051/epjconf/202124804015
Models for Managing Production Systems of Machine-Building Enterprises Based on the Development and Using of Their Digital Twins
1
LLC “Digital Systems Factory”, Moscow, Russia
2
Moscow State Technological University “STANKIN”, RU-127055, Moscow, Russia
3
LLC “AAMC”, RU-121471, Moscow, Russia
4
PJSC «DSPP», RU-141700, Moscow region, Dolgoprudny, Russia
* Corresponding author: npa@digitalfabrika.ru
Published online: 26 April 2021
The paper discusses the goals and objectives of creating digital twins of the production system of a machine-building enterprise. The data structure of the information model of the production system of a machine-building enterprise, which is the basis for building a digital twin, is presented. The paper shows the main approaches to managing a production system based on the construction of its digital twin. It is revealed that along with traditional approaches to PS management by forming recommendations in terms of PS engineering and its operation, the choice of the most rational PS management algorithms that take into account the peculiarities of the production process organization and ensure the formation of production schedules that take into account PS reliability indicators has a great potential. It is proposed to use a specialized language of DPML to describe the information model of the PS through the “product-process-resource” paradigm, which ensures the coordination of the processes of forming recommendations in terms of engineering and operation of the PS, as well as the choice of the most rational algorithm for managing the PS.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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