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Explore what digital twins really are, why they matter now, and how they help companies reduce risk, test earlier and improve complex production systems.
Digital twin is one of those terms that almost everyone has heard, however few define it the same way. Ask three experts, and you’ll likely get three different answers. And that’s not necessarily a problem. It just reflects how broad the concept is and how many ways it can create value.
Still, one thing remains consistent:
A digital twin is about taking something physical – a machine, a production line, or even an entire factory – and creating a virtual version of it that you can test, explore, and improve.
And that changes how companies work.
Taking digital twin from concept to capability
In its simplest form, a digital twin allows you to move work from the physical world into the virtual one. Instead of testing directly on machines, stopping production or building expensive prototypes, you can simulate, test and refine in a digital environment.
That means fewer surprises when things go live and fewer costly mistakes late in the process.
As one perspective from the field highlights, a digital twin only becomes a true “twin” once the physical system exists. Before that, it’s closer to a design model. But the value is already clear: you can start testing much earlier and keep improving throughout the lifecycle.
Why companies are investing now
The growing interest in digital twins is not driven by technology alone; it’s also driven by very real operational challenges.
Companies are using digital twins to:
- Reduce risk by testing changes before implementing them
- Speed up development by validating systems earlier
- Lower costs by minimising physical prototypes and waste
- Improve quality through better testing and iteration
- Enable remote work by diagnosing and solving issues without being on site
- Reduce test material during design, manufacturing and commissioning
In complex production environments, this can be the difference between a smooth launch and months of troubleshooting.
It’s not about perfection – it’s about learning
One important point is that digital twins are not perfect replicas of reality. You don’t need 100% realism to create value.
In many cases, companies can test most coding, sequences and interactions digitally – while leaving some physical aspects to be validated later. The key is that the most critical issues are identified early, when they are cheapest and easiest to fix.
A different way of working
Perhaps the biggest shift isn’t technical, but cultural.
Digital twins enable a more experimental, iterative way of working:
- Teams can test ideas quickly
- Explore different scenarios
- And learn through simulation before making decisions
It’s less about getting everything right the first time and more about creating the environment to improve continuously.
Or put differently:
You move from reacting to problem to designing better outcomes.
In conclusion
Digital twins are not just a tool. They are a way to rethink how we design, test, and operate complex systems. For companies working within production, automation, and industrial processes, it’s not really a question of if you should start using these technologies, but rather how to start.
If you're exploring how digital twins could support your operations, the first step is not technology; it's identifying where testing, risk, or complexity slows you down today.
Want to talk about your needs and how a digital twin can support your business? Reach out to Lotte Høeg Jul Jensen, Head of Digital Twin & AI at ProjectBinder:
