• Data won’t show the ideal behavior, rather reality creates a distorted image of it –> AI identifies patterns and builds a stochastic model.
  • Algorithms extract an idealized picture of the batch processing, but considers realistic variations.
  • Model learns sequence of individual steps and properties of each step.
  • Tolerances for each measurement and other properties, such as valid durations, are derived for batches and individual steps in the batch.