SBIR Phase I:Uncertainty Analysis of Manufacturing Process Models

This Small Business Innovation Research (SBIR) Phase I project will create a software system for performing uncertainty analysis of manufacturing process models. When the models are large, or when there are many parameters, even the best Monte Carlo, or importance based sampling methods for uncertainty analysis can be prohibitively expensive. One consequence is that systematic uncertainty analyses are often never carried out. This project will implement a new method for uncertainty analysis, based on polynomial chaos expansions, that can determine the probability density functions of the response and can identify which of the parameters contribute most to uncertainties in outcomes. The commercial potential of this project has broad application to such fields as circuit design, risk management, allocation of experimental resources, chemical plant design and operation of production systems.