Technologies and applications that are merely desirable but do not contribute to the creation of value are useless in the field of energy. Businesses can improve project execution, operational efficiency, sustainability, and revenue by taking an all-encompassing approach to developing the digital thread and digital twin.
In this article, I will define the terms “digital thread” and “digital twin” in the context of the energy industry and outline how these concepts can be used to aid in the design, construction, and maintenance of the assets that will power the future.
The pandemic caused by COVID-19 exposed numerous flaws in the energy industry’s project operations. We quickly became aware of the numerous challenges associated with remotely operating plants and maintaining efficiency regardless of location or time. It became abundantly clear that we needed to find a way to standardize our assets’ operations, reduce repetitive tasks, and boost our efficiency. It quickly became clear that the use of digital technology was critical.
Despite the fact that technology is present in almost every aspect of modern life, its effective application is not as widespread. People working on digital transformation and the implementation of new technologies frequently fail because they do not understand the challenges that their industry faces.
Workers in the industry who are familiar with its systems, processes, and challenges may or may not understand newly developed technologies. Furthermore, there has been a clear lack of an integrated approach to both greenfield and brownfield projects; during the project’s design, construction, and operation phases, a large number of different engineers and stakeholders are involved, and there is a risk that data will be easily lost during handovers.
Having great technology is never enough on its own if businesses are unable or unwilling to make effective use of the technologies they have.
In various fields of business, the terms “digital thread” and “digital twin” are interpreted differently. Michael Grieves developed the initial concept in 2002, with the primary goal of utilizing the capabilities provided by digital environments to carry out simulations. NASA created the first application of this technology in 2010, but since then, a plethora of other applications have been created, including Google Maps, smart cities, autonomous vehicles, simulations of health care, construction planning, and many others. Every industry has its own set of definitions and examples of application.
Many of these applications are focused on data processing. In the energy sector, however, the data we work with can be either static or dynamic. Because the operations phase accounts for roughly 80% of the total project life cycle, having real-time data is critical. The creation of a class library, which is the categorization of data and information for each piece of equipment, asset, and project, marks the start of the project’s gradual information handover. This serves as the foundation for the digital thread:
The digital thread refers to the information that must be acquired as well as the progressive handover of that information throughout the life cycle of a project. This could include historical data as well as information gathered from various systems during the project’s engineering and construction phases. As more information is gathered and additional data dimensions are created throughout the life cycle of a project, the digital thread becomes more developed.
The process of correlating data from multiple systems to produce a single, unified source of truth is referred to as “digital twin.” A digital twin is also a system of systems that represents correlated data in a digital context, also known as “the digital asset.” Unlike a digital thread, which focuses on the actual collection of information, a digital twin considers how that information about its surroundings should be presented.
The technologies known as digital threads and digital twins have names that sound very similar, are used in settings that sound very similar, and are inextricably linked.
In the energy industry, the digital twin is referred to as the digital plant. The development of a system of systems necessitates the correlation of data from various systems and timelines. The digital thread assembles the digital asset one bit at a time. This starts with metadata and evolves into a progressive thread that incorporates external environmental data, AI- and ML-powered predictive information, and other components to build a comprehensive model.
We have evolved the concept of a digital twin since its inception by introducing various stages of maturity. The use of digital twin technology is possible at an extremely early stage in the project’s life cycle. While a 3D model may appear to be as simple as a point cloud at first, it has the potential to become more complex through the addition of data and the application of newly developed technology. This would add more informational and operational dimensions.
There are several things that can be done with the information after it has been correlated and represented: On top of this data correlation, we can perform analysis, intelligence gathering, and application development. AI allows for the creation of insights as well as the incorporation of additional functionalities.
Oil and gas operators want remote monitoring and autonomous operations, which can be accomplished with the data brain, also known as the digital twin. Once a digital twin is created to represent information in context, it can help inform how designs are reviewed and create immersive tools to help visualize plants before they are built. These advantages can be realized once a digital twin is created.
The energy sector has been investing in automation since the 1990s. Despite advances in digital technology innovation, the sector’s processes have evolved at a slower pace. After all, technology accounts for only 10% of innovation, with people accounting for the remaining 90%. Having said that, there has been significant technological advancement in the energy sector in recent years, particularly in the areas of conventional and renewable energy.
The sudden need to be able to perform tasks remotely from any location at any time had a significant impact, as needs always trigger solutions. This is because solutions are always triggered by needs. We have recently seen numerous industry applications of AI in IIoT data to generate insights and improve worker safety.
The primary goal of the digital thread is to collect more data while utilizing newer technologies. Drones, robots, 5G, satellites, laser scanning, and other new technological advancements have powered the digital thread and enabled advanced operations. Because of all of these brand new technologies at the helm, as well as a shift in mindset brought on by the global pandemic, innovation and transformation are no longer a slow and steady process; rather, they are accelerating and transforming into a more comprehensive shift.
Establishing a standard definition for both the digital thread and the digital twin is unquestionably necessary in the field of energy; however, what matters are the potential outcomes.
The more valuable the data in the digital thread, the more potential solutions you can obtain; however, the specific requirements you have will determine which ones are required. We need to achieve an integrated life cycle in a digital environment, where people, processes, assets, and systems are linked for efficient project execution and unified operations using AI and advanced technologies.
In this sense, digital twins are undeniably the key to lowering costs, minimizing downtime, and lowering emissions while improving efficiency and safety, all of which are critical to achieving a sustainable future.
When it comes to digital twins, the question of why is no longer relevant; instead, the emphasis has shifted to how the technology should be applied appropriately. It will be followed shortly by the development of norms and standards that will allow the technology to be successfully implemented. The need is undeniably present, and fortunately, so are the investment opportunities. At this point, the only thing left to do is persuade communities to play an active role in the implementation of the solutions.