This paper extends the stack validation algorithm in a probabilistic way. In other words, we introduce a new model for stack validation when the production parameters are random variables and the result is compared with a confidence interval. The major outcome of this simplified probabilistic model is to determine random variables merely by mean, variance, and skewness. This straightforwardly enables some direct, fast and consistent calculations by using certain properties of these moments.
Categoric simulation of production flow | Signal | Stochastic processing times | Probabilistic stack validation