Smart manufacturing is coming, and those wanting to realize benefits sooner may find directional guidance through the use of digital twins.
Digital twins may help manufacturers cross the Internet of Things divide, and allow manufacturers to innovate supply chain practices, monitor remote assets and improve overall decision-making, according to ABI Research. These virtual models of processes, products or services, which ABI sees as a manufacturing game changer, can be used to test processes, detect issues and simulate scenarios that will be deployed on the physical model.
While the idea of digital representations of physical objects has been around for decades (think of CAD models), new and emerging technologies and their migration into the manufacturing sector will up the game and advance digital twin technology to “digital mastery,” noted ABI in a statement.
Right now, though, according to an ABI survey of 455 respondents, only four percent of manufacturing companies have digital twins in operation; 83% have begun investigating the technology and 29% plan to start trials in the next 12 months.
What will fuel adoption is increasing IT/OT convergence, in which data-centric computing IT systems are integrated with operational technology (OT) systems. These converged systems will be used to monitor events, processes and devices and help companies adjust enterprise and industrial operations and practices.
According to ABI’s recent big trends summary, the intersection of analytics, augmented reality (AR) and digital twin technologies (digital and physical convergence) along with the confluence of storage capabilities is driving “greenfield technology decisions in a brownfield world.”
In a recent webinar, ABI Research’s principal analysts Ryan Martin and Pierce Owen talked about some of these smart manufacturing trends, and how digital twin’s physics-based simulations may provide better and more accurate insights about what is happening inside machines, creating high value for mission-critical equipment.
“There is interest there, but many of these technologies can be married together when you compare what’s being planned and what lies ahead in the future,” said Martin. He added that using some of these technologies together can usher in more opportunities for monitoring and control, automation and intelligent data management.
Although companies are heading in this direction, there are gaps between strategy and practice: Companies want to standardize, optimize and scale their endpoint infrastructures but they lack a common set of tools to operationalize the intended efficiency improvements, the analysts said.
And, the human factor is something to consider as well. “Longer term, it has to do with wrapping the analytics not just around technology but also around people and process,” Martin said.
To get beyond some of the challenges, Pierce suggested some best practices for transforming manufacturing.
First, as with all other IT and IoT implementations, companies will want to align from the top down and the bottom up; chief digital officers and other similar liaisons could help smooth out those issues.
Organizations also need to balance their distributed and consolidated computing capabilities, he said. Starting at the edge of where companies are now—with near real-time, centralized, on premise control—and maximizing it with the cloud, which provides deep learning and interdepartmental integration capabilities.
Scaling one platform, one application at a time is important as well. “Have a performance target in mind before you scale the application. If you hit the target, commit and deploy the application,” Pierce said, adding that if companies don’t set targets and deployment commitments projects die along the way.
What role will digital twins play in your smart manufacturing strategy? Tell us in the comments below.