Using Digital Twins for CBM+ and RAMS Decision Support

Vincent Mendoza, John V. Morgan, Marlene Haag
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Abstract

The following paper discusses a digital Reliability, Availability, Maintainability and Safety (RAMS) ecosystem that provides model-based insight into the core elements of RAMS in order to enable CBM+ and the real-time health state of a system. The case focuses on using the combined capabilities of various Digital Twin models for data-driven, informed decision support and technical analysis. With reliability regularly an afterthought during design and development we argue that if taken into account during these phases systems will be more predictable, reliable and will limit the users' exposure to consequences. The example is based on a fictional system – the DeLorean Time Machine from Back to the Future – to illustrate that the solution is system agnostic and may be applied to any type of complex, technical system and any industry space.
利用数字孪生进行CBM+和RAMS决策支持
下面的文章讨论了数字可靠性、可用性、可维护性和安全性(RAMS)生态系统,该生态系统提供了对RAMS核心元素的基于模型的洞察,以便启用CBM+和系统的实时健康状态。该案例侧重于使用各种数字孪生模型的综合能力,以进行数据驱动、知情的决策支持和技术分析。在设计和开发过程中,我们认为如果在这些阶段考虑到可靠性,系统将更可预测、更可靠,并将限制用户对后果的暴露。这个例子是基于一个虚构的系统——《回到未来》中的DeLorean时间机器——来说明解决方案是系统不可知论的,可以应用于任何类型的复杂技术系统和任何工业空间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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