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468 Industrial Wastewater Treatment, Recycling, and Reuse
• Undocumented assumptions. (This is extremely important, and it is
strongly suggested that assumptions made at each stage of the modeling,
simulation, and analysis exercise be documented thoroughly.)
• Using the wrong input probability distribution
• Replacing a distribution (stochastic) by its mean (deterministic)
• Using the wrong performance measure
• Bugs in the simulation program
• Using standard statistical formulas that assume variable independence
• Initial bias in output data
• Inadequate sensitivity analysis and case studies to cover scenarios of
interest
• Poor schedule and budget planning
• Poor communication among the personnel involved in the
simulation study.
In a nutshell, a mathematical model can
• Help technical personnel understand process behavior in an easy
manner.
• Run various scenarios—both steady state and dynamic—in simulations
without making any actual changes in the plant.
• Effectively and automatically optimize the process through the use of
sophisticated algorithms.
12.1.2 Water Integration (Pinch Analysis)
In the previous section we discussed the use of process simulation to develop
accurate heat and mass balances and derive stream properties for a given
flowsheet. The water network is an integral part of the process flowsheet,
and thus this information can be used to direct efforts to reduce the con-
sumption of water as a utility.
Figure 12.1 depicts the overview of a water minimization technique in
an industry. Opportunities for water minimization can be considered at four
levels (Buehner and Rossiter, 1996):
(1) Process changes
Replacing the technology employed in a process can reduce the inher-
ent demand for water. Examples might be replacing a wet cooling sys-
tem with air coolers or increasing the number of stages in a washing
operation. Sometimes it is possible to reduce water demand by chang-
ing the way existing equipment is operated, rather than replacing or
modifying it.

