This workshop provides several exercises that may be used to further explore the on-line use of batch data analytics for fault detection and quality parameter prediction. The operation of the mixer and blender in the Saline process will be observed using the data analytics on-line view.
Step 1: Open the Batch Data Analytics web-based interface and select the Overview tab to see the current status of the process.
Step 2: Select a batch that is shown to have a fault condition and then select the Fault Detection tab. Click on the point in the trend that shows maximum variation in T2 or Q statistics.
Step 3: Examine the parameters that contributed the most to the fault condition. Based on the parameter trend, identify the process disturbance that is the source of the fault condition.
Step 4: Select the Quality tab to determine if the fault had an impact on the quality parameter, product % solids.
Step 5: Repeat steps 2, 3, and 4 for the last four fault conditions shown in the Overview. Identify the process disturbance that caused the fault condition.