Skip to content

Home / Monte Carlo / Analyzing The Model / dpm vs # out of spec

dpm vs. # out of spec

When using Tolerance Allocation, Optimize (Parameter Design), and Sensitivity Analysis, you will be given the opportunity to select between "dpm" and "# out of spec" for each output.

Optimization Control

If you select dpm, the analysis will be performed using the calculated value of defects per million by integrating the area under the Normal (Gaussian) curve.

If you select "# out of spec", the analysis will be performed using the number of defects observed out of specification limits during the Monte Carlo simulation, scaled to 1,000,000.

If the output is normally distributed (based upon the histogram during Expected Value Analysis), you should use dpm; otherwise, use # out of spec.