Robust Design and Reliability

Design robust, reliable products with our module dedicated to uncertainty management. 


Product performance is often determined by factors that are difficult to predict in the design stage.

These factors, known as uncertainties, may include manufacturing errors, material property variation, or external conditions in which a given product is operated in real life. 

Take these uncertainties into account (and manage them effectively) from the early stages of design. This way, your designs can turn into products that perform consistently well (robustness) and have the lowest possible failure rate (reliability). 

Apply robust and reliability-based optimization to avoid opting for designs that perform well on paper, but under-perform in real life.
Find the most cost-effective solution without compromising on the factors that might undermine the perceived overall quality of the product.
Pick Your Method
Pick one of the advanced numerical methods offered by our Robust and Reliability-based Design Optimization module. The uncertainty is quantified stochastically based on the method of your choice (Monte Carlo, Latin Hypercube, Polynomial Chaos). 
Minimize Failure
The results are considered in the optimization process to find the best compromise between the performance and stability in presence of uncertainties. In the case of reliability, the optimization consists in searching for a design solution that minimizes the failure probability.
Be Confident with Approximations
Benefit from accurate uncertainty quantification with less computational effort. Our Adaptive Sparse Polynomial Chaos Expansion method is able to reduce the number of samples required for the uncertainty quantification without sacrificing the accuracy of the analysis.