Digital Twin as the best solution for your business
Modeling and simulation to design, optimize and monitor devices, systems and processes.
What is a Digital Twin?
A Digital Twin is a mathematical model that reproduces the functioning of a physical object or a system.
The Digital twin behaves like a real product and provides answers based on user-defined parameters, with accurate levels of fidelity and reduced calculation times. We can reproduce a single component, or simulate an entire process by relating different multiphysics models.
Whether it is a car, a chemical plant, a machine, a single component or an entire system, Dofware can create a mathematical model capable of reproducing the same behavior of the real object.
For the multidomain simulation and the model-based design of these dynamic systems, Dofware uses Dymola, based on the open source Modelica® modeling language.


Why Digital Twin?
The virtual product is useful throughout the real product life cycle, for different purposes.
The Digital Twin today is mainly used for the production phase: for process planning, for monitoring operations and for predictive maintenance.
For example, it can be used to perform predictive analysis of the wear of a component, or to simulate a machine or an entire industrial plant to carry out employee training or maintenance simulations.
An innovative use is to exploit the digital twin also in the design phase and for the improvement of existing assets, to study and validate new ideas. Define the best solution to best meet the project requirements and predict the responses of the product to a change of variables by testing directly on the digital twin.
Realize physical-mathematical models in 1D able to reproduce the behavior of products, components and software to evaluate their performances even before the construction of the prototypes or the validation of the code.
Benefits
What are the benefits of the Digital Twin at different stages of your product life cycle?

In the pre-design and design phase, the Digital Twin can tell us if and how a product will work
Technological integrations and interconnection
More and more efficient communication systems allow the continuous exchange of information between the real system and its Digital Twin.
The IOT platforms can expand the range of services by integrating our co-simulation solutions (DT-Orchestrators that manage federations of Digital Twins that communicate with each other), with the real system and with company’s management systems
For the modeling of the Digital Twin Dofware can combine and integrate different approaches and methodologies such as Machine Learning and AI, physical data, simulations with lumped parameters, CFD, FEM, etc.
A Digital Twin…everywhere
Discover the opportunity for dynamic and real-time simulation on any platform: cloud, edge computing, mobile devices, embedded platforms.
With Dofware you can have all this in your hand.
Our algorithm assimilates and processes the parameters set by the user and provides a quick and reliable simulation as a result, running the virtual model of the physical product on any platform, according to the user’s needs and the complexity of the model used.



An example?
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Some application examples
Multiphysics simulation finds application in any field, from a single component to an entire process.
In the automotive industry, for example, we can estimate the consumption of a vehicle’s brake pads, or check the stability of a racing car by setting different suspension settings. We can also evaluate a user’s driving style based on the real time data collected by his smartphone.
In the industrial field we can model and simulate the operation of an entire industrial plant in order to predict the maintenance interventions.
Virtual models can estimate the energy needs of a system (as was done for the HOME project) or to design it virtually in order to define its best configutation and performance (an example of modeling of solar panels to estimate energy production).
In the HVAC world we can analyze air quality and define the indoor comfort through real-time monitoring and simulations.
