A Methodology for Managing the Effect of Uncertainty in Simulation-Based Design

Simulation-based design has become an inherent part of multidisciplinary design as simulation tools provide designers with a flexible and computationally efficient means to explore the interrelationships among various disciplines. Complications arise when the simulation programs may have deviations associated with input parameters (external uncertainties) as well as internal uncertainties due to the inaccuracies of the simulation tools or system models. These uncertainties will have a great influence on design negotiations between various disciplines and may force designers to make conservative decisions. In this paper, an integrated methodology for propagating and mitigating the effect of uncertainties is proposed. Two approaches, namely, the extreme condition approach and the statistical approach, are developed to propagate the effect of uncertainties across a design system comprising interrelated subsystem analyses. Using the extreme condition approach, an interval of the output from a chain of simulations is obtained, while the statistical approach provides statistical estimates of the output. An uncertainty mitigation strategy based on the principles of robust design is proposed. The methodology is presented using an illustrative simulation chain and is verified using the case study of a six-link function-generator linkage design. Nomenclature a vector of system objective c.d.f. cumulative distribution function f response surface model (function) F vector of simulation function g vector of system constraint p.d.f. probability density function RSM response surface model S displacement of slider w weighting factor x vector of design variable x vector of nominal value of x y vector of linking variable z vector of system output ∆x vector of range of x α the maximum pressure angle ε ε ε ε vector of error model ϕ crank angle µ µ µ µ vector of mean value σ σ σ σ vector of standard deviation ψ rocker angle 3