Multivariate simulation assessment for virtual metrology

To reduce cost, this paper proposes a system architecture to simulate and assess the multivariate of equipment properties. The architecture integrates the Monte Carlo simulation, the Neural Network model and the sensitivity analysis to construct a virtual metrology system. By assuming the property's probability distribution, the architecture generates the extreme input data to supplement the actual data for enhancing the model accuracy and estimating the property trend. An industrial case applied to validate the proposed system architecture.