Digital twins and IOT: integrating the physical and virtual worlds
This video of Dr Grieves presentation at the conference that presented him with a “Game Changer Award” does not have his slides, but it doesn’t really need it.
He outlines that there are three aspects to any digital twin:
- The Physical – the asset and its environment
- The Virtual – the twin and a virtual environment
- Connected with a bi-directional flow of data
He outlines that digital twins make sense because:
- Failure is costly
- It makes sense to move work from the physical world into the virtual world because “atoms are getting more expensive, but bits are getting cheaper”
- The cost of information is less than the cost of wasting physical resources, and this gap is increasing all the time (Moore’s Law)
- Since around 2015, we’ve had the computing capability to deliver effective digital twins (producing practical returns that exceed their investment). Again, this will continue to dramatically increase.
He suggests there are three types of digital twin:
- Prototype. From concept to design.
- Instance. As built.
- Aggregate. Learning from multiple assets to predict failure/resource waste.
Why it’s relevant to Nextspace
Apart from being a relatively comprehensive speech by the acknowledged “father” of digital twins, this video is of benefit to Nextspace Partners because it discusses the close relationship between IoT and digital twins, and because of a few comments Dr Grieves makes (paraphrased):
- Aim your digital twin strategy at the computing power that will come, not for today’s technical ability
- The need for fast cycle times – IoT capturing data from the real world and feeding it into the virtual world
- The need for integration of IOT and AR to generate actionable information and comparison – sensing where things are at (with the asset but also its environment) and measuring the gap between that and where we want things to be (our goals)
- The need to cause action – either responding autonomously through the twin orby communicating getting humans to act
- The need for cybersecurity - a massive concern
Dr Grieves says digital twins should address three key use case categories:
- Interrogative(giving me information)
- Predictive (giving potential futures with % probabilities so we can avoid adverse events)
- Learning(from previous asset and environment analysis, seeking to identify correlation and causation)
Finally, DrGrieves talks about the various development stages of digital twins and enabling technology since the early 2000’s. He labels our current phases as “Conceptual”and says that data interoperability is the greatest challenge right now. Beyond that he sees the next digital twin phase as “Replication” which is essentially the federation of digital twins.
For more from Dr Grieve’s you can follow him on LinkedIn
