What is a Digital Twin and Why It Matters
A refinery is a high stakes environment with no room for error.
Operators must learn how to run production facilities, but training on the real asset would be risky. A minor error could put workers in harm or cause downtime, costing hundreds of thousands or even millions of dollars.
So, plant operators turn to digital twins.
“A digital twin is a replication of a physical process and assets within a replicated virtual environment,” said engineer Leila Ait Ali, who has worked with operator training simulators since 2013.
The use of digital twins has become so significant today, that Gartner named it one of the top 10 high-tech trends in 2019.
Here’s how digital twins can be used:
For operational efficiency
Digital twins give visibility on the actual process against expected parameters. The difference between the actual and the expected values gives better insight into areas that are underperforming or performing incorrectly. That enables operations to make changes and achieve ideal operations.
This will lead to improved:
- Efficiency: Improved data quality and security; continuous monitoring and optimizing of plant assets
- Cost reductions: Faster operational readiness; direct and easy access to information
- Revenue growth: Faster and collaborative decision making
In the same way pilots practice takeoffs and landings with a flight simulator, plant operators practice starting up and shutting down the plant with a simulator, Leila said.
“We replicate the process and the logic of the plant,” she said.
Those simulators use 3-D graphics, virtual and augmented reality and data modeling to create a digital replica.
“We make sure that when they sit in front of that simulator, it’s like they’re sitting in front of the real plant,” Leila said.
Digital twins can anticipate maintenance.
NASA became one of the first to formally use the digital twin concept in 2002 to assist in the operation, repair and maintenance of rockets.
Similarly, digital twin technology can be used in an oil refinery.
For example, pumps, compressors, heat exchangers and other pieces of equipment in a refinery need to be maintained.
Digital twins can utilize data collected on those pumps to predict when they would start degrading in performance.
Operators and maintenance teams know when to perform maintenance to proactively address issues before they become a problem. That helps avoid a plant shutdown and can help determine where there are “opportunities to reduce downtime, prolong maintenance intervals, and capture untapped throughput potential,” according to our case study.
“When you have data and information on equipment, it makes it easier for you to maintain it and ensure it is at its peak performance,” Leila said.
An oil refinery, power generation station or gas processing plant are high-risk locations, Leila said.
Among the risks are fires or explosions, so safety is paramount.
Using digital twins for training makes sure operators know all safety procedures. Digital twins also can anticipate potential risks and create optimal design.
Digital twins can help industrial companies drive transformation and stay competitive.
“We are working toward the best software in this area,” Leila said.