You might have heard of the term ‘Digital Twins‘ before. First coined by Dr Michael Grieves who called it Doubleganger - it is considered an essential building block for the 4th industrial revolution. Digital Twins are duplicates that can simulate the real-world conditions in a virtual environment. A bit like playing Flight Simulator. But is much more than the blueprint of the physical object, as it needs to understand all of the dynamics of how a device is put together. With the collection of sensory data from the real world twin (including the ageing effects), we can project possible outcomes. The simulation of specific conditions in the virtual world is the safest way to test challenging scenarios. The result of this testing and playback in the real world leads to the optimal performance of the company assets.
Where would you use the digital twin?
Manufacturing is a large user of virtual reality and digital twins in the production process. Car manufacturers can capture the behavioural and operational data and the performance of a car far ahead of the construction of the actual vehicle. Using the vast amount of real-world data that has been collected with sensors on test cars and project this on a new virtual model.
The next step is the digital twin of your car. Daimler is working on an application that creates a digital twin for every car they produce. The data will be used to manage the life cycle of the car - and has a deep integration with the data layer in the car (ECU, CAN, ADAS etc). Together with the behaviour of the rider and the environmental conditions that influence the state of the vehicle.
Other applications that use Digital Twin technologies:
Construction 4.0 & Energy 4.0
Digital Asset Inspection
Building Information Modeling (BIM)
Utility Asset Management
Decentralization with Distributed Energy Resources (DER)
What do we need for this to work?
Analytics are applied at every step in the process. The data that is required from a simple IoT device or a complex device such as an oil rig is massive.
We need to collect real-time data and operational data. It needs to have quality and be predictive in nature. The data has to be open so that it can be transformed, combined and shared. This is a dynamic process and its parameters change over time. It can be used during the design, build and operational phase of the product.
Once the data is collected it will be ready for the cognitive sensory - what I call the AI for IoT. (A simple example of a cognitive sensor is the sniff test. When you go for your MOT, the sniffer is placed up the exhaust to check how harmful the emission is)
The last part is the presentation. This is where the representation takes place and actionable data is presented.
Here are 2 examples that show this in a design and in an operational phase of a product.
Digital twins have been at the heart of the current industrial revolution. It combines new technologies and processing advancements (such as Cloud GPU) to make this a relatively affordable and scalable service that is ready for a broader business acceptance.
Gulf Consulting has a wide variety of solutions for digital transformation and digital asset management. Contact us today, to discuss how this can be used in your organisation