Page 396 - Design of Simple and Robust Process Plants

9.6 Project Methodology for Operation Optimization 383
. Savings of a factor 0.05 up and to 0.1 times the raw material cost gap between
actual and theoretical feedstock cost.
. The factor 0.05 was used for systems with 1±5 independent variables for opti-
mization.
. The factor 0.1 was used for systems with a large (25)number of independent
variables.

Reduction in operating expenses (including utility costs)will be factored by 0.05 to
0.1 of the total operating expenses. Like the factor for feedstock saving, this factor
will similarly depend on the number of independent variables for OO.
A more fundamental approach was developed by Hennin and Perkins (1994)and
by Loeblein (1997)and Loeblein and Perkins (1996). This approach has been vali-
dated by Vafiadis (1998)and Loeblein and Perkins (1999). The method is based on
the availability of an optimization model applied for off-line OO. The ultimate opti-
mization results can be determined if the constraints and the parameters are deter-
mined precisely over its operational range. The back-off for actual CLO from the
ultimate optimization can be determined based on two factors; the uncertainty of
the optimization, and the control performance. In other words, the average deviation
from the ultimate optimum for an on-line optimization depends on; the covariance
of the statistical uncertainty in the parameters and the measurement errors, and the
regulatory control performance. The theoretical approach has been verified by the
application of Monte Carlo simulations.
This method assumes that an off-line optimization model is available and that the
constraints and parameters are known, next to the measurement accuracies. This
information is not available at the start of a OO. project. For the determination of
the savings of a CLO in respect of an off-line optimization, it will have its benefits.
The economic evaluation of an OO project must be based on a cost±benefit anal-
ysis. The technical evaluation regarding manpower, software, hardware and mainte-
nance consequences should be clearly considered as these might have technical and
organizational impacts. Site or company standards might be affected by decisions
regarding software and hardware.

9.6.2
Scope Definition: Step 1

The definition of the scope should include the following elements based on the fea-
sibility study results:
. Type of project (static/dynamic; optimization/scheduling).
. Type of optimization (off-line/closed loop).
. Type of software for flowsheeter/reactor modeling/executive.
. Preliminary selected DOFs for optimization
. Boundaries of the project.
. Cost, timing and manpower allocation.
. Projected savings.