Intelligent Multiphysics Generative Design for Advanced Manufacturing
Intelligent Generative Design for Advanced Manufacturing
TOffeeAM is a Cloud Platform for Optimization and Simulation
Our automated design software enables you to optimise your engineering component to maximise its thermo-fluid and structural performance.
Specify your optimisation targets and let the code design your part!

What is multiphysics generative design?
Generative design or topology optimization is a mathematical approach that relies on the calculation of a metric that describes the performance of a component. The component design is changed according to its performance value until a maximum is reached. The system only requires you to input the space available for the component, its working conditions (such as temperature or fluid velocity), and the kind of optimisation you are searching for (for example the lowest pressure loss between entry and exit). The software will design the optimum components for you in three dimensions.
Multiphysics Generative Design is the evolution of this approach, combining several physical problems together with manufacturing constraints.
What is the interest of using Additive Manufacturing?
- Print from digital prototypes
- High flexibility in design and materials available
- Cut down on logistic, waste of materials and energy waste

What do you win by increasing design efficiency?
- Less fuel consumption
- Less CO2 and NOx emissions
- Higher performance
- Increased reliability
Aerospace
- Coolant system
- Valves
- Combustion chambers
Achieve up to 30% increase of efficiency for more complex coolant systems.
Automotive
- Power system cooling
- Fuel cells
- Vented brakes
For a commercial car, higher efficiency means less fuel consumption. In the case of electric cars, controlling the temperature of the battery can be made more efficient.
Energy
- Pipes
- Mixers
- Cogeneration system
Re-design your components for improved efficiency. Complex systems such as valves can be reduced to a single component using generative design.