Page 457 - Design of Simple and Robust Process Plants

444 Chapter 11 Optimization of an Integrated Complexof Process Plants and Evaluation
11.4.5
Ranking Order for Design of Simple Units

Apply ranking order of simplicity in units design, as for:
Reactors: liquid phase versus gas phase; homogeneous versus heterogeneous;
adiabatic versus isothermal; tubular reactor versus CSTR.
Distillation: In increasing level of complexity for:
One- or two-component distillation; flash, stripper, absorber, dephlegmator, stand-
ard distillation.
Three-component distillation: one column configuration; side draw, divided wall
column, side stripper, dephlegmator, two sequential columns.
Piping. Minimize the terms in the complexity function of piping

C = f (M) (N) (O) (Q),
where M is number of lines, N is number of valves, O is number of piping items,
and Q is number of interconnections.
Instruments: Apply a defined instrument selection procedure based on the
approach: ªbetter a good reliable instrument then lots of unreliable onesº.

11.5
Process Design Based on Reliability

The design of simple and robust process plants is based on ªsingle and reliable com-
ponents unless¼º. The quantitative bases to support this approach can be found in
reliability engineering and reliability databases.
Reliability modeling is a mature technique to form a quantitative basis for process
design.
Reliability studies are a tool to optimize the design of process plants based on the
single-component philosophy. It has proven to be of high value, and now rational
decisions can be taken around reliability and availability design issues.
Reliability availability and maintainability (RAM) specifications form a quantita-
tive base for the purchase of equipment and supplies. Ram specifications require a
partnership between supplier and receiver to obtain the maximum benefit.

11.6
Optimization of an Integrated Complex of Process Plants and Evaluation
of its Vulnerability

Higher levels of process integration at a complex of process plants can bring consid-
erable cost savings in logistic cost as well as operational cost. The logistic require-
ments for such a complex can be optimized based on reliability engineering tech-
niques. The vulnerability of a complex can be quantified and design alternatives