Digital Twins
One of the most powerful applications of knowledge graphs is via digital twins. Digital Twins have rapidly gained traction amongst the manufacturing, aeronautical and energy sectors for their ability to monitor and react to rapidly changing scenarios with little to no margin for error.
The ability of knowledge graphs to capture complex concepts and their associated relationships means that they are perfectly suited to support complex digital twins across a range of industries.
“If you want to model the full diversity of the real world, you need something like a graph to really do that” – Ora Lassila
What is a Digital Twin?
A cycle diagram here (if Amit allows it)
Digital twins are especially powerful for generating and exploring ‘parallel world’ scenarios.
Via The World Avatar™, CMCL is able to leverage the ‘base world’. This is a collection of existing datasets describing the world as it exists in real-time.
How can they be applied?
A cycle diagram of the labs here (if Amit allows it)
An example of a digital twin unlocking innovative new possibilities is via autonomously collaborating self-driving labs.
Self-Driving Laboratories are part of a a rapidly growing field that could potentially unlock rapid advances in material design, drug discovery and more. By combining artificial intelligence with automated robotic platforms, experiments can be planned and carried out with far greater speed than before, releasing highly-skilled researchers from repetitive tasks.
However, challenges with scaling the technology have so far hindered progress and limited potential. The immediate need for vaccines during the Covid pandemic highlighted the need for research to be more agile than ever.
The World Avatar™ and the Derived Information Framework are ideally placed to tackle this challenge, and were applied to connect physical labs in Cambridge and Singapore. The connected laboratories were able to collaborate and rapidly move towards a combined set of results.
Case Study: Self-Driving Labs
Agents within the framework cascaded information across a dynamic knowledge graph.
Results informed a dynamic Design of Experiment agent, which then continuously suggested new experimental conditions to be executed across both labs.
As experiments were carried out and results gathered, a Design of Experiment (DoE) agent autonomously identified new experimental inputs and passed those parameters to the labs. These points can be seen in the far right chart.
In this case study, the linked labs were able to rapidly (<3 days) generate a Pareto front displaying cost-yield optimisation, a common goal across industry.
More information about this research can be found in this paper.
Connected Digital Twins
Leveraging The World Avatar™, CMCL goes beyond with Connected Digital Twins. Actions in sectors rarely result in impacts constrained within the original domain. Typically, decisions made in one area result in wide reaching consequences in other sectors. Previously, due to technological barriers, these were not considered.
However, via the Distributed Data Architecture, CMCL are able to connect digital twins and data from various sectors and organisations whilst ensuring full data ownership and security.
CMCL are able to deploy Digital Twins to provide insights and automated control applications
If you wish to know more about how we could support you and/or your business, feel free to contact us.