Synchronizing Process Variables in Time for Industrial Process Monitoring and Control

Abstract The use of soft-sensors in industry is becoming more popular, as they allow for the prediction of critical product qualities from process variables in real-time. The requirement for this that all process variables are dynamically synchronized is often not met. Although different methods for dynamically synchronizing process variables are reported, no critical comparison of these methods is available. In this study we show that the choice in synchronization method significantly influences a soft-sensor's accuracy. From the methods studied, median filtering using a moving window with a width of 168 minutes placed before the target times led to the highest sensor accuracy for the production plant studied, a method not reported in literature. This optimal width is remarkable, as the total processing time of the plant is 30 minutes. This suggests that changes in the physical state of the plant can affect the production quality than one might expect.