Missing flow detection

Missing flows can occur for the following reasons:

• Missing movement when an operator has forgotten to record a transfer of material from one tank to another during the course of day.

• Mis-specified movement when an operator may have inadvertently specified the wrong source or destination tank for the movement.

• Large process leaks in the unit, pipeline, tank, and so on.

• Wrong flow line connection in the data reconciliation model.

These missing flows can pose a major threat to the material balance because the DR algorithm tries to force the imbalance to zero in the nodes with missing flows.

Example 1 of missing flows

For example, this diagram shows the critical problem due to the missing flow in the “R_MTBE_C4RA” balance point.

There are some missing movements pertaining to the process but the data reconciliation algorithm will attempt to balance the process balance point unless we enable missing flow detection.

The reconciled values of most of the flows around this balance point show a big difference from the associated measured values. This will cause many of the measurements to be treated as faulty when, in fact, they were valid.

Figure: Color-coded flows

However, if you enable the missing flow detection feature, which is performed before data reconciliation, the results will be much better, as shown in the figure below.

Figure: Results when missing flow detection enabled

The Missing Flow Detection step automatically detects the balance point with missing flows and then eliminates it from the reduced list of balance constraints to be met. That is, the process that has the missing flows is allowed to remain unbalanced.

As you can see in the figure above, if the “R_MTBE_C4RA” process is allowed to remain unbalanced because it has missing flows, the reconciled values of most of the flows around this balance point are close to the measured values.

In a real plant, it is very likely that a combination of faulty measurements and missing flows will occur concurrently. It is very difficult to detect faulty measurements prior to determining which flows are missing. Therefore, missing flow detection is done by the DR algorithm before faulty measurement detection.

Example 2 of missing flows

In this example, “ME2” is a faulty measurement and the “NO5” balance point has missing flows. If we run data reconciliation without the missing flow detection step, the reconciled value of most flows are much different from the measured values. Furthermore, the “ME7” and “ME8” flows may be wrongly categorized as faulty measurements in the faulty measurement detection step even though these two flows are well matched to surrounding, redundant measurements.

But, if we run data reconciliation with the missing flow detection step, the “NO5” balance point is detected as one with missing flows and therefore its balance constraints are not enforced. Next, the faulty measurement detection step detects “ME2” as a faulty measurement. Therefore, the reconciled values in the rest of the flowsheet end up being calculated as close to the measured values.