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Robust Design and Reliability

Deliver high-quality products while considering all uncontrolled factors during the production or the operating phase with our technology for uncertainty quantification.

Robust Design and Reliability

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 product development with our Robust Design and Reliability technology. This way, your designs can turn into products that perform consistently well (robustness), have the lowest possible failure rate (reliability) or minimized quality loss (Taguchi-based quality engineering approach).

Manage uncertainties efficiently and deliver high-quality products


Robust Design Optimization

Find the best compromise between the design performance and its stability with our state-of-the-art stochastic approach. Apply robust optimization to avoid opting for designs that perform well on paper but under-perform in real life conditions.


Reliability-based Design Optimization

Define the best design solution (within a failure region) while specifically considering the unavoidable effects of uncertainty. Perform Reliability-based Optimization to minimize the failure probability.


Taguchi Quality Engineering

Benefit from Taguchi-based quality engineering method when minimizing product quality losses is more cost-effective than trying to control their source.

Tailored for your company needs

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Many engineering problems require to predict defects and failures of a product during the design stage in order to avoid economical losses in the market. With our modeFRONTIER solution, you can manage these uncertainties by choosing a robust, reliability or Taguchi quality engineering plan. Then, according to your scenario, configure parameters and objectives, apply numerical methods to investigate the behavior of uncontrolled factors (i.e. manufacturing errors, operating conditions, external factors) and deliver high-quality optimum design solutions.