The Issue -
Process monitoring solutions, such as statistical process control, monitor and control a process to make sure it operates efficiently, resulting in high quality and productivity while minimizing waste. Add real-time capabilities, and SPC can identify process deviations to fine-tune industrial operations on the fly. In theory, that should be enough to hold process performance to exacting standards. But is it? Or is it just delivering an incomplete view of process health?

In an asset-heavy industrial environment driven by high-volume, high-speed Industrial Internet of Things data, there could be inconsistencies and errors in the process parameters under observation. Is the asset itself underperforming, or are its sensors delivering incorrect data? Are the sensors operating correctly? Or are network issues skewing the data? Any of these could mislead operations or quality managers with false positives and false negatives and lead to unnecessary, misinformed or missed corrective action.