(238b) Estimation of Product Robustness: Prediction of Manufacturing Variability
AIChE Annual Meeting
Tuesday, November 18, 2014 - 8:55am to 9:20am
This presentation will describe an approach to leverage process models and historical data of potential
sources of variability (materials, process parameters, and analytical measurements) to estimate the
process performance under defined manufacturing control strategies.
Using Monte Carlo tools, the process performance is estimated as a distribution of the possible outcomes
of the measured process quality attributes. The outcomes are generated from a Bayesian network that
integrates all the sources of variability associated with the process.
Applied to process models generated during process development, this framework will be useful in
providing a statistically sound, quantitative level of risk associated with process performance under
different control and monitoring strategies as well as informing technology transfer/validation and
process robustness decisions.