Its methods may be used on other types of systems subject to accumulated variation, such as mechanical statistical tolerance analysis pdf electrical systems. Typically these dimensions and tolerances are specified on an engineering drawing.
In performing a tolerance analysis, there are two fundamentally different analysis tools for predicting stackup variation: worst-case analysis and statistical analysis. Worst-case tolerance analysis is the traditional type of tolerance stackup calculation. The individual variables are placed at their tolerance limits in order to make the measurement as large or as small as possible. The worst-case model does not consider the distribution of the individual variables, but rather that those variables do not exceed their respective specified limits. This model predicts the maximum expected variation of the measurement. Designing to worst-case tolerance requirements guarantees 100 percent of the parts will assemble and function properly, regardless of the actual component variation. The major drawback is that the worst-case model often requires very tight individual component tolerances.
Worst-case tolerancing is often required by the customer for critical mechanical interfaces and spare part replacement interfaces. When worst-case tolerancing is not a contract requirement, properly applied statistical tolerancing can ensure acceptable assembly yields with increased component tolerances and lower fabrication costs. The statistical variation analysis model takes advantage of the principles of statistics to relax the component tolerances without sacrificing quality. Each component’s variation is modeled as a statistical distribution and these distributions are summed to predict the distribution of the assembly measurement. Thus, statistical variation analysis predicts a distribution that describes the assembly variation, not the extreme values of that variation. This analysis model provides increased design flexibility by allowing the designer to design to any quality level, not just 100 percent. There are two chief methods for performing the statistical analysis.