One of the major developments in simulation modelling in recent times, and a significant component in the maturation of Industry 4.0, is the digital twin.
Many may wonder whether talk of digital twins is just more hype. The answer is a categorical no. Digital twins are here now, and are already revolutionising key areas of the manufacturing, supply chain and logistics industries with Gartner recognising them as one of their Top 10 Strategic Technology trends for 2019.
But what is a digital twin and what can they help businesses accomplish?
At its simplest, a digital twin is a virtual representation or replica of a physical object, system, process or environment, built from real-time data collected by sensors. The result is a highly complex model that is a one-to-one match for its physical counterpart, providing unparalleled insight into operational lifecycles, and allowing for new testing and optimisation scenarios.
In fact, digital twins have been in existence for many decades, but the rise of the Industrial Internet of Things has brought a renewed attention to their use as an integrated tool for planning, testing, observing and predicting how equipment is performing, and will perform over time.
Early adopters reap the advantage
In short, they can help manufacturers identify potential faults, adjust and improve performance in real-time, and integrate machine learning for targeted optimisations on the fly. Their potential to improve business processes and create long-term value is now beyond question.
Organisations like Rio Tinto have already recognised their potential for creating ‘intelligent mines’, which has captured the attention of the resources sector Australia-wide. And their use isn’t simply limited to the industrial and mining space either, with one US hospital – Hamilton Health Sciences – recording a 900 percent improvement in cost savings after leveraging digital twin technology to eliminate bottlenecks in the patient handling.
Other potential applications are in the technology design space, where real-time machine learning can be applied in the testing of advanced engines across various real-world and simulated scenarios – from anywhere in the world. The possibilities are vast, and the competitive advantages available to early movers are very real.
Want to learn more about how your organisation can take advantage of digital twin technology? Contact the Simulation Experts at SMS and get started on tomorrow’s technology breakthroughs today.