为生产企业发展数字孪生

IF 0.6 Q4 BUSINESS
V. Makarov, A. Bakhtizin, G. Beklaryan
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引用次数: 15

摘要

本文提出了一种利用模拟方法开发生产企业数字双胞胎的新方法。描述了数字双胞胎的概念,它是一个集成系统,汇集了遗传优化算法类的仿真模型、数据库和智能软件模块、数据挖掘子系统等。文章介绍了不同生产公司的仿真模型示例,特别是典型的装配厂和典型的石油生产企业。第一家公司开展活动,将具有自身特色的单个组件组装成产品。为了描述这样一个企业的行为,使用了代理和离散事件建模的方法。第二家企业在现有领域生产具有个人特色的碳水化合物原料。由此开发的综合模拟模型与面向主题的数据库和优化模块相集成,这些模块有助于控制各个生产企业的技术和资源特征。这些模型的开发是使用AnyLogic和Powersim模拟系统进行的,这些系统支持基于代理的建模和系统动力学方法。我们在这里展示了使用现代模拟工具为制作公司创建“数字双胞胎”的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing digital twins for production enterprises
This article presents a new approach to developing digital twins of production companies with the use of simulation methods. It describes the concept of digital twins as an integrated system that aggregates simulation models, databases and intelligent software modules of the class of genetic optimization algorithms, subsystems of data mining, etc. The article presents examples of simulation models of different production companies, in particular, a typical assembly plant and a typical oil production enterprise. The first company carries out activities to assembly products from individual components with its own individual characteristics. To describe the behavior of such an enterprise, methods of agent and discrete-event modeling are used. The second enterprise produces raw carbohydrate materials at existing fields with individual characteristics. The integrated simulation models thus developed are integrated with a subject-oriented database and optimization modules that facilitate providing a control of the technological and resource characteristics of the respective production enterprises. The development of these models was performed using AnyLogic and Powersim simulation systems that support agent-based modeling and system dynamics methods. We demonstrate here the possibility of creating ‘digital twins’ for production companies using modern simulation tools.
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