Page 395 - Design of Simple and Robust Process Plants

382 Chapter 9 Operation Optimization
9.6.1.8 Performance measurement
The performance measurement is discussed in Section 9.4. In this step, it is impor-
tant to determine the development costs and the additional instrumentation
required to perform this functionality.

9.6.1.9 Projected cost and time planning and manpower resources
The determination of all the costs involved in the implementation of an OO project
are a requirement, and to assess completeness, the following list is prepared:

. Modeling software costs to be included; licensees for process simulator, reac-
tor models, optimization executive, model development.
. Control software costs to be included; licensees, redesign basic controllers
and its programming, model-based controller development and installation.
. Hardware costs involve instrumentation, computer platform for MBC, and
optimization.
. Implementation costs and validation.
. Maintenance costs, mainly updating of models.
Time planning is an important factor, as the total execution time might be more
than 18 months. Also, the involvement of company-related manpower should not be
underestimated, in terms of availability and cost.

9.6.1.10 Project savings and evaluation
Savings are determined in perspective of the maximum achievable savings for the
objected optimization. The approach for the different OO projects will differ slightly.
Scheduling projects will determine the savings related to the maximum achiev-
able operational schemes (no waiting times between batches), but including flush-
ing steps if required.
Transient operational savings will be estimated by comparing the actual and mini-
mal transient times that determine the off-grade production, as well as the capacity
gain during transients. In general, the minimization of the transient operation is
constrained in the process. Minimization might be restricted, in case of co-mono-
mer grades, by the feed capacity of one of the co-monomer systems to obtain the
new required concentration in the reactor system.
Continuous operational savings can be split into capacity maximization and
conversion cost reduction. Capacity maximization must be estimated from the
constraint analysis with different feedstocks and product states, in addition to
the potential capacity gain by taking advantage of varying meteorological condi-
tions (e.g., temperature day and night cycle). Capacity gains on the order of 5%
are easily achievable, particularly in the case of multiple (three to five)con-
straints, while alternative feedstock options (two to three)may increase this by
up to 10%.
Conversion cost savings are estimated as a percentage of the conversion cost.
White (1999)used the following approach, based on experience: