Defining Digital Thread vs. Digital Twin Energy
With a holistic approach to building the digital thread and digital twin, companies can realize improvements in project execution, operational efficiency, sustainability, and revenue.
In the energy sector, there is no point in nice-to-have technologies and applications; they need to build value. With a holistic approach to building the digital thread and digital twin, companies can realize improvements in project execution, operational efficiency, sustainability, and revenue.
This article will define the digital thread and digital twin in the energy sector, as well as outline how they can be used to help design, build, and maintain the assets that will power the future.
The COVID-19 pandemic highlighted many gaps in project operations in the energy industry. We quickly saw the many challenges of remotely operating plants and being efficient from any location at any time. It became clear that we had to find a way to unify the operations of assets, reduce repetitive tasks, and improve efficiencies. It became apparent that digital technology was key.
While technology is everywhere today, however, applying it in the right way isn’t nearly as common. We see frequent failures related to digital transformation and the implementation of new technologies because the people working on them don’t understand the challenges of the industry.
Meanwhile, those in the industry who have the knowledge of the systems, processes, and challenges do not necessarily understand emerging technologies. What’s more, there has been a distinct lack of an integrated approach to both greenfield and brownfield projects; many different engineers and stakeholders are engaged during design, construction, and operation, and the thread of data can easily be lost during handovers.
Having great technology alone is never enough if companies are unable or unwilling to apply them effectively.
Defining the Digital Twin and Digital Thread
There are many definitions of “digital thread” and “digital twin” related to different industries. The first concept was developed by Michael Grieves in 2002 and was aimed at using the digital environment to run simulations. The first application was by NASA in 2010, but, since then, there have been many others: Google Maps, smart cities, autonomous vehicles, health care simulations, construction planning, and more. Every sector has its own definition and use cases.
Many of these uses focus on processed data. In the energy sector, on the other hand, we have both static and dynamic data. With the operations phase accounting for about 80% of a project life cycle, real-time information is fundamental. The progressive handover of information during a project starts with the development of a class library—the classification of data and information for every piece of equipment, asset, and project. This forms the basis of the digital thread:
- Digital thread—the information that needs to be acquired and the progressive handover of that information through the life cycle of a project. This could be historical data, as well as information from the engineering phase or the construction phase from various systems. The digital thread matures as you gather more information across the life cycle of a project and create more dimensions of data.
- Digital twin—the correlation of data from different systems to create one single source of truth; a system of systems where correlated data is represented in digital context (i.e., “the digital asset”). Where a digital thread is all about gathering the information itself, a digital twin is about how to display that information in context.
When it comes to digital threads and digital twins, the technologies have similar names, are leveraged in similar environments, and are inextricably connected.