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Robustness Evaluation

optiSLang quantifies the robustness of designs by generating a set of suitable design variations on the basis of scattering input variables. Optimized Latin Hypercube Sampling and the quantification of every input variability on the result variation by the Coefficient of Prognosis (CoP) ensures the reliability of the variation and correlation measures with a minimum of required design variants.

Best Practice

  • Definition of all possibly influencing uncertainties as the crucial input of a robustness analysis
  • Predefined distribution function types and an input correlation matrix to support best possible definition of scattering input variables
  • Automated generation of optimized Latin Hypercube Samples (LHS) to scan the robustness space with minimal input correlation error
  • Identification of the most affecting input scatter for every response and quantification of input variable influence using the Coefficient of Prognosis (CoP)
  • Quantification of robustness by the histogram of result values including fitting of distribution function, approximation of sigma level and violation probability

Methods

  • Stochastic input variables with distribution types and input correlation
  • Optimized Latin Hypercube Sampling
  • Fitting of distribution function in the histogram of result values
  • Approximation of Sigma margins
  • Approximation of violation probability

Postprocessing & Visualization

  • Histograms to illustrate scatter of result values
  • Linear correlations matrix, nonlinear CoP based correlation matrix, MOP and  CoP plots
  • Distribution fitting, Sigma values, violation probabilities
  • Traffic light plot to check the violation of limit values of critical responses

Distributors

optiSLang is sold worldwide. A list of our distributors can be found here.

Your contact person

Dr.-Ing. Johannes Will

Fon: +49 (0) 3643 9008-30
Fax: +49 (0) 3643 9008-39