Although digital twins have recently emerged as a clear alternative for reliable asset representations, most of the solutions and tools available for the development of digital twins are tailored to specific environments. Furthermore, achieving reliable digital twins often requires the orchestration of technologies and paradigms such as machine learning, the Internet of Things, and 3D visualization, which are rarely seamlessly aligned. In this paper, we present a generic framework for the development of effective digital twins combining some of the aforementioned areas. In this open framework, digital twins can be easily developed and orchestrated with 3D connected visualizations, IoT data streams, and real-time machine-learning predictions. To demonstrate the feasibility of the framework, a use case in the Petrochemical Industry 4.0 has been developed.
翻译:虽然数字双胞胎最近成为可靠资产表述的一个明确替代物,但发展数字双胞胎的现有大多数解决方案和工具都是根据具体环境量身定制的,此外,实现可靠的数字双胞胎往往需要设计各种技术和范式,如机器学习、物的互联网和3D直观化等,这些技术和范式很少完全吻合。在本文中,我们提出了一个将上述某些领域结合起来的有效数字双胞胎发展通用框架。在这个开放框架内,数字双胞胎可以很容易地与3D连接的可视化、IoT数据流和实时机器学习预测一起开发和组织。为了证明框架的可行性,在Petro化工业开发了一个使用案例4.0。