Hydrocarbon Processing - January 2021 - 48

Process Optimization
Now is the time to calculate the next
point on the journey to higher yield.
TABLE 2 depicts this process. From the c1
and c2 coefficients, the direction of steepest ascent is calculated per Eq. 5, i.e., from
p1 to p2 in FIG. 9. The step size defines a unit
circle in transformed coordinates (dotted
circle in FIG. 9). Taking a step along the
path of steepest ascent equivalent to an
additional +1 units brings us to our new
design center, p2. From there, four supplemental points are added (s5-s8 ) to comprise the next factorial series, which forms
the basis for the next iteration. To calculate
the actual process settings there, the transforms are inverted in Eqs. 21 and 22:
T[°C] = -0.89 × 5[°C] +
300[°C] = 296°C

(21)

and
P[kPa] = 0.45 × 10[kPa] +
500[kPa] = 505[kPa].

(22)

Therefore, the design center has been
moved from p1 (i.e., 300°C and 500 kPa)
to p2 (i.e., 296°C and 505 kPa). The process yield data is now collected. In this

way, additional points along the path of
steepest ascent are calculated.
Takeaway. EVOP results in continual
process improvement. Although the current method requires only spreadsheet
software, EVOP may also be automated
as part of a process control strategy. Indeed, EVOP is one of many statistical
techniques used to optimize processes
and make experimental and research
strategies more effective and efficient.
Such techniques minimize the time and
cost of experimental investigations and
are a worthy pursuit for the researcher,
process engineer or operator.
LITERATURE CITED
1 Box, G. E. P., " Evolutionary operation: A method for
increasing industrial productivity, " Journal of the Royal
Statistical Society, Series C, 1957, online: https://
www.gwern.net/docs/statistics/decision/1957-box.
pdf
2 Online: http://asq.org/quality-progress/2015/01/
statistics-roundtable/evop-an-underused-technology.html
3 Colannino, J., Modeling of combustion systems: A
practical approach, Taylor and Francis, Boca Raton,
Florida, 2006.

4 Box, G. E. P. and N. R. Draper, Empirical modelbuilding and response surfaces, John Wiley & Sons,
New York, 1987.
5 Colannino, J., Modeling of combustion systems: A
practical approach, Chapter 1, " Introduction to
Modeling, " and " A Linear Algebra Primer, " ; and
Chapter 3, " Experimental Design and Analysis, "
Taylor and Francis, Boca Raton, Florida, 2006.
JOSEPH COLANNINO is a registered
chemical engineer in the state of
California. He has more than 30 yr
in the HPI/CPI and specializes in
leading process teams to profitable
innovation. He has more than 100
patents pending and granted, and
many of his innovations are still in revenue-producing
service. Mr. Colannino has authored or co-authored
several books in combustion, pollution control and
experimental design. He was formerly head of research
and development for John Zink Co. LLC, and CTO
for a Seattle-based startup. Now CEO of Colannino
Consultants, he consults in pollution control and
teaches industrial courses on process optimization,
improving R & D structure and output, and the art of
technical presentation and communication. He received
his BS degree in chemical engineering from the
California Polytechnic University at Pomona and holds
an MS degree in knowledge management from the
University of Oklahoma with an emphasis in leading
research organizations. A spreadsheet containing all
the calculations discussed in this article, as well as
additional explanatory text, is available from the author
by request at colanninoconsultants@gmail.com.

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