The strength of the Monitor computer program lies in its ability to track the performance of a network over time and to identify significant trends. This is not a simple task. A refinery cannot just measure the furnace inlet temperature (FIT) each day and plot it. Other factors, such as different crudes, varying product slate requirements and changing ambient conditions will mask the real trends. 

These variations  can happen on a day-to-day basis and will cause changes throughout the network.  Their effect on the measured FIT may totally swamp any changes due to fouling. We need a way of determining the real effect of the fouling resistances on the FIT which is not affected by process changes.

The way this is done is by Normalisation of each case's results onto a single Base Case. The fouling resistances calculated in each case are applied to the feed and other conditions in the Base Case. Repeating this for a range of cases over a period of time gives a set of Normalised Furnace Inlet Temperatures (NFIT) whose trend is due only to changing fouling resistances.   

How significant can this difference be?

Results from monitoring a real refinery crude preheat train are shown here. The comparison between the actual temperature (FIT) of the furnace run-up stream and the NFIT is significant. NFIT indicates a steady decline in performance; FIT gives no indication whatsoever.

Automated Running ] Data Input ] Database Storage ] Economics ] Fluid Definition ] Fouling Calculations ] Import ] [ Normalisation ] Output ] PFD ] Data Reconciliation ] Splitter Ratios ] Thermodynamics ]