A Robust Design is a design which reacts in its most important properties marginally to variations of the input parameters, i.e. the scattering of the output parameters lays in a feasible field. The robustness is analysed by a stochastic parameter study. There, the values of the parameters are chosen by the methods of the so called Monte Carlo simulation. The result of this study is the variation of the output parameters. Requirements for the study are: A parametric model for the simulation, the distribution functions of the input parameters and a software for calculating the parameter values and for controlling the simulation loop. In both models (the beam in bending and the shaft) the distribution functions of the resulting values as well as the spread of the distributions correlate directly with the distribution functions of the input parameters. Although the probabilities that the values lay within certain intervals are identical, the spread of the distributions varies significantly. The spread of the uniform distribution is obviously higher than those of the other two. Considering that the uniform distribution can be used as a worst-case scenario.
Impact of distribution functions of input parameters on the quality of robustness analysis in simulation
Auswirkungen der Verteilungsfunktionen der Eingangsparameter auf die Qualität der Robustheitsanalyse bei der Simulation
2006
9 Seiten, 12 Bilder, 4 Tabellen, 3 Quellen
Conference paper
English
Simulation-Based Robustness Analysis of On-Board Diagnostics Functions
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