An engineering system is typically described by a large number of parameters. Engineers face the difficult challenge of specifying appropriate values for these parameters by using their knowledge, expertise and judgment. It has to be determined how to arrive at the best overall design by making the right compromises, without sacrificing critical attributes like safety. But it is almost impossible to take into account all of these variables simultaneously due to the sizing and complexity of a typical design task.
FEAC, by using several algorithms that help identify the most suitable candidates, taking into account multiple objectives and performance trade-offs provides the best possible solution.
There can be a number of motivations to optimize a design.
- Achieve higher magnetic field within a safe structure, for superconducting magnets industry
- Reduce the overall weight, save fuel, increase safety, improve the range and increase the payload for aerospace & automobile industry
- Greatly improve efficiency for renewable energy industry
- Reduction of the overall weight of a structure
- The most efficient use of material, possibly leading to reduction in material cost
- Design space exploration
- Parameters correlation
FEAC uses design optimization techniques and finite element analysis to overcome such problems, providing the best possible solution to our clients. A good design starts with identifying the relationship between performance and design variables. Once the design has been explored and the correlations and sensitivities have been understood, the final step is to optimize the design. Design optimization is the process of finding the best design parameters that satisfy the project requirements. Parametric variations of CAD parameters, material properties, loading conditions and joint/bolt locations enable to easily explore the design space with what – if studies. We typically use design of experiments (DOE), statistics and optimization techniques to evaluate trade-offs and determine the best design.
Design optimization often involves working in multiple design environments in order to evaluate the effects that design parameters have across interrelated physical domains. It can be applied during the product development stage to ensure that the final design will have the high performance, high reliability and best raw material usage leading to low weight and low cost. Alternatively, optimization methods can be applied to existing products to identify potential design improvements.