“Digital twin” is not a new term, but paired with advancements in AI, it’s increasingly valuable in transforming industrial operations, creating additional business value. The digital twin, which produces an evolving profile of an asset or process in a plant, captures insights on performance across the plant lifecycle (process design, operations and maintenance).
It is also made increasingly more intelligent by AI agents, to the point where it can prescribe actions in the physical world, so that companies can reconfigure, in real-time, with fact-driven choices, alternate processes to mitigate issues like plant downtime or bottlenecking.
Providing a digital view into areas like planning and scheduling, demand models, distribution models, and control and optimization, and improving efficiency of those operations through prescriptive action, leads to amplified business profitability (perhaps the number one benefit that comes to mind, for many, when considering implementing digital twins).
But profitability is only part of the story.
In this question and answer session with AspenTech’s Ron Beck, we further explore digital twins and how they are transforming industry.
With the present market uncertainty, volatility and questions around future economic outlook, every industrial organization is looking for new ways to drive efficiency and be more profitable but, most importantly, to ensure safe operations. With plants running in unfamiliar low-turndown situations, technology is the gateway to that goal.
Managers see digital as a key way to maintain insight into equipment health and integrity without the usual workers in the plant. The digital twin and AI are not the aspirational future they once may have been – they are proving to bring impact to the bottom line in many industrial organizations.
Most importantly, they provide insights that no human could on equipment health and future safety risk. Leveraging both digital and AI, in combination with one another, will put businesses in a sound position to tackle some of the age-old challenges in plant operations in new and more effective ways.
The digital twin creates virtual copies of physical locations, plant processes, business processes as well as assets, and, paired with AI, enables plant operators to find value within plant data that they can then leverage to drive improvement across various operations.
The two technologies essentially capture everything that is happening in the plant and, with the data insights they provide, can help plant operators reach better operational decisions and lead to greater operational excellence.
Additionally, economic outlook aside, there is growing pressure on the industrial world right now to find greener ways to make product and be more sustainable companies with lower or even zero carbon intensity. Coincidentally, there is a major role for both digital twins and AI to play in making a greener world a reality.
Drilling down into the digital twin concept, the beauty in it is its ability to give businesses an alternative lens through which to see their operations, providing them with insight into a variety of plant and process scenarios and helping uncover where the greatest efficiencies lie.
Through data mining and leveraging domain expertise, AI serves to essentially power digital twins, making them increasingly intelligent. The new efficiency comes from (a) less need for people walking into dangerous areas of the plant, and for them to be transported to remote areas (b) mobilizing the explosion of asset data for new insights and ability to optimize across multiple objectives and (c) improve plant uptime through better prediction of future failure and the ability to maintain asset health efficiently.
For plant operations, beyond increasing uptime, the benefit of the digital twin is most felt in the scheduling, design and planning phases of the plant and plant processes. Utilizing digital twin modeling to design, find or utilize processes that will result in improved efficiency leads to tremendous operational gains. The question “what if” is something that can be rigorously analyzed through rapid consideration of a wide range of possibilities – it is the question every digital twin essentially solves for.
But also, feedback from operational data to the design function now enables designing a new process line after comparing it to the operability of previous designs and, consequently, designing for better reliability, safety and operability.
Maintenance is another area in which we see the advantage of leveraging both AI and the digital twin. Digital agents powered by AI can predict, weeks in advance, impending asset failure and the causative factors. Digital Twins can then prescribe process actions to preserve equipment health so that industrial organizations can minimize plant downtime.
Sustainability requires a rethinking of what constitutes optimal operations. In addition to safety, throughput, quality, and cost, now zero carbon, circular economy, and emissions become critical criteria. Technology here is a key driver of sustainability.
The digital twin is a powerful enabler of better sustainability transparency, reporting, measurement and optimization. From an energy management standpoint, virtual replicas of different plant processes put a spotlight on processes and equipment that use the most energy and contribute to unnecessary energy waste.
The same concept holds true for plants looking to curb the output of emissions and effluents.
Another interesting benefit of the digital twin is its ability to help train plant operators virtually. There are many high-risk plant scenarios, including startups, shutdowns, and emergency response procedures. The plant environment requires expertise to pilot effectively, and these infrequent situations are rarely practiced for sufficiently. Virtual training simulators have a huge benefit, like a pilot flight simulator does for pilots.
A final note, I am often asked does this mean there will be fewer workers in industrial settings? What digital and AI technologies will do, is free up the valuable knowledge worker, operator and maintenance staff to perform more value-added work, leading to better execution of business strategies, and more agile decision-making, at all levels, in an increasingly volatile world.
The future process industry organization will be more effective and efficient, with the staff performing different work that provides competitive advantage and more sustainable operations.