Implementing Digital Twin principles can help businesses achieve predictive maintenance, detect anomalies, perform root cause analysis, and provide online dashboards and reports for managers, operators, and QA, while also providing the possibility for continuous improvement through iterative integration of information.
Digital Twin is a software component that mimics behaviour of an arbitrary physical system.
Unlike physical systems that are closed, have hidden states, give partial, noisy, and delayed information, the twin:
- is open and 100% transparent
- provides all actual and historical data through API in unified model
- suppresses measurement noise, model errors
- estimates hidden state information from historical states and actual observations of the original physical system
- data is available even during infrastructure outages and before the real data has arrived (prediction)
- acts actively – autonomously issues alerts and events when something interesting happens
Digital Twin in Manufacturing
- predicts future development – probability distribution of machine defect (e.g. predictive maintenance)
- detects anomalies – detection of exceptional behavior
- fires alerts and watch for important events – hitting tolerance limits
- root cause analysis – what impacts quality or caused machine defect
- online dashboards and reports for managers, operators and QA
- machine heterogeneity – different vendor, age and level of wear
- hidden states – some states are not physically possible to measure
- unstructured, disconnected data in different format – data has different data models, is not correlated, is stored in data silos
Digital Twin in Healthcare
The latest research says that 80% of the diseases can be prevented. Imagine that you are going to a doctor who will make you a unique “digital twin” – your unique digital image that will based on your health history, special tests and ongoing measurements and will give an objective assessment of your health.
More over, the digital twin will be able to track, detect anomalies, predict trends in your health and let you or the doctor to act in advance. Imagine that the system is constantly learning from the latest research and experience that has helped people with a similar diagnosis anywhere in the world.
Digital Twin for Living
Every building – house, office or whole city part – is a physical system with complex internal dynamics and many evolving variables. Typically, only a small subset of this information is visible and the building is de facto a black box. If enough variables with sufficient sampling frequency gets available, you can create digital model that behaves similarly to your building. If you then connect the model with the building you get the physical system and its digital twin synchronized.
Now imagine that you connect data from all other interacting systems such as people, outside whether, forest nearby… You can go further and start wisely influencing the complete ecosystem through actuators and strategic planning to achieve environment that is green, healthy, energetically and financially sustainable .