Daily wafer fabrication in semiconductor foundry depends on considerable metrology operations for tool-quality and process-quality assurance. The metrology operations required a lot of metrology tools, which increase FAB's investment Also, these metrology operations will increase cycle time of wafer process. Metrology operations do not bring any value added to wafer but only quality assurance. This article provides a new method denoted virtual metrology (VM) to utilize sensor data collected from 300mm FAB's tools to forecast quality data of wafers and tools. This proposed method designs key steps to establish a VM control model based on neural networks and to develop and deploy applications following SEMI EDA (equipment data acquisition) standards.