Quality Monitoring with Predictive Models

Environment conditions such as temperature, humidity etc play a vital role in some manufacturing processes. Viscosity of the final product in paint manufacturing depends on several parameters including the humidity inside the building.

Detecting Thresholds
As a first step to ensuring quality, we would need to identify the ideal operating conditions. eRED Edge is hooked up to all the sensors on the factory floor to gather environmental data and flow in eRED edge is created to read Process data from a database stored on premise. eRED Edge then overlays (merges) the Process data with environmental data and pushes it to a cloud server. An operator runs analytics on this data in the cloud to detect failure conditions and identify environment thresholds. This threshold is fed back to eRED Edge for prediction.

Predicting Failures
eRED Edge reads the new threshold values and triggers alarm, raises events or takes proactive actions such as suspending the machines when environmental conditions outside of the normal range is detected depending on the flows designed by the operator.