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Composition Tracking
Technology Description








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Inlibra uses Time Slicing – with a variety of tank modeling methods, minimum composition percentages, and automatic movement detection -- to deliver a tracking mechanism head and shoulders above the competition.

Time Slicing
To correctly simulate blending of materials when a tank has incoming and outgoing movements during the same accounting period, you need to divide the accounting period into time slices and perform the blending of materials at the end of each time slice.

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Tank Calculation Methods
The following tank blending types, described below, are available:

logo bug  Homogenous

logo bug  Heterogeneous
      FIFO (First In, First Out)
      LIFO (Last In, First Out)

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Homogenous Tank Method

The homogenous tank method is suitable for well-mixed tanks. The algorithm conceptually mixes the feed and product at the start of each time slice.

Homogenous Tank
Figure 1 - Homogenous Tank

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Heterogeneous Tank Methods
FIFO Method

The FIFO (First In, First Out) method is suitable for representing pipeline segments.

Pipeline segments with significant capacity must be represented in your plant model. Inlibra allows you to do this using a tank object with special property settings.  For pipeline segments the fluid quantity is fixed; they don’t fill and drain like tanks.

Pipeline segment representations enable you to cope with different plugs of material in the line in any one transaction. Each plug comes out in the same order it went in; there’s no mixing of material between plugs.

FIFO Method
Figure 2 – FIFO Method

LIFO Method
The LIFO Tank Method permits you to model a last-in, first-out tank without mixing.

LIFO Method
Figure 3 – LIFO Method

Minimum Composition Percentage Calculations
The minimum composition percentage allows for elimination of trace amounts of fluid from the analysis when their quantity becomes insignificant. The definition of significant varies, so this is a configurable parameter. When quantities fall below the minimum percentage, the model adjusts volumes so that you don’t lose any of the overall volume. Rather than eliminating the insignificant fluid volumes entirely, the trace amounts are distributed among the other fluids within the tank. This essentially models real operations and the true treatment of trace volumes.

Automatic Movement Detection
Automatic Movement Detection in Composition Tracking automatically detects the movement events between tanks using real time tank inventory data. The graph below shows how to detect the time and quantity of movement events from the real time trend of tank inventory data.

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Figure 4 – Movement data in inventory

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The movement data are automatically detected from real time tank inventory data.
Generation of movement from inventory change
Figure 5 – Generation of movement from inventory change

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Figure 6 shows movement data automatically generated from 10-minute interval inventory trends of each of the tanks in the display. The movement data fully represents all real movements that took place.

automatically detected movements
Figure 6 - User display showing automatically detected movements

After automatic movement detection, Inlibra CT automatically detects the movement between tanks as well as receipt and feed movements to the processing unit. The blue line in the right diagram is the movement line, which Inlibra CT automatically detected from the 10-minute interval inventory data of each tank. These detected movements equal exactly what could be manually derived by analyzing inventory change as well as what would have been metered, had metered data been available. Users are spared the effort of manually entering the movement data, which also eliminates movement logging errors.

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Data Reconciliation
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Composition Tracking
   Introduction >
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Smart Objects
Stockpile Tracker
   Introduction >
   The Problem >
   What ST Provides >
   What Your Plant Needs >
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   Goals of ST Design >
   Modeling Method >
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