1. 9
ACHEMA
ACHEMA 2006, which takes place from May 15–19, 2006 in Frankfurt am Main, Germany, is one of the
leading exhibitions for the process industries. As a leading international event for equipment suppliers
to the HPI, ACHEMA in 2006 will present technology developments, offer worldwide contacts and
new business networks. The event is expected to attract some 4,000 exhibitors and 200,000 visitors
from all over the world.
This event, held every three years, will be covered in 2006 with a special supplement in the May issue
of Hydrocarbon Processing. This supplement will continue over 18 years of coverage on ACHEMA
by Hydrocarbon Processing and will offer the unique country-by-country wrap up of industry activity.
Special rates do apply. Please contact your representative for full details.
Closing date for advertising is April 5, 2006.
THE DEMISE AND KEYS TO THE RISE
OF PROCESS CONTROL
Occasionally we get a “landmark” article that we know will be referenced for decades to come
—this article is one of them. The author, Dr. Pierre Latour, is an acknowledged world expert
on, and one of the originators of, modern advanced process control. Currently president of
CLIFFTENT, Inc., he was a cofounder of Biles & Associates and Setpoint, and has worked for
DuPont, Shell Oil, DMCC and AspenTech. Dr. Latour holds BS and PhD degrees in chemical
engineering from Virginia Polytechnic Institute and Purdue University respectively. Following the
practices he outlines in this report will substantially improve the value of process control.
Closing date is February 5, 2006.
DESIGNER DIESEL
Europe wants diesel badly. It wants the efficiency of diesel, and it wants fuels that
can be manufactured from renewable resources. But because of concerns about
microscopic diesel emissions, it expects future diesel to be cleaner than ever.
Designer diesels are a blend apart. Refiners will face a major blending challenge.
How Europe’s refiners, catalyst manufacturers, process licensors, additives vendors
and engineering/constructor companies respond to this challenge will dictate in large
part how successful Europe is in meeting its goal to protect the planet’s climate, while
protecting its city populations from airborne pollution.
From the unparalleled editorial team at Hydrocarbon Processing, Designer Diesel 2005–
2010, examines the policy aims, the market drivers and the work-a-day challenges that
face Europe’s process industry in providing abundant supply, on-spec for the demands
of the coming five years.
Circulation: Europe
Closing: December 2005
Distribution: January 2006
Photo courtesy of, GASTECH 2005
2. DEMISE/RISE OF PROCESS CONTROL BONUSREPORT
HYDROCARBON PROCESSING MARCH 2006
I 71
umerous articles, editorials and ads in the past few years
described trouble in the commercial practice of process
control and suggested remedies like better quality infer-
entials, basic loop tuning, operator training, process knowledge,
algorithms, models, engineers, instruments, integration and
management faith. The business is fragmented, floundering and
declining.There is no consensus on the cause or remedy, but some
suggestions to improve the industry are provided.
The full business promise of process control, instrumentation,
automation, closed-loop optimization, information technology
(IT) integration and HPI computer integrated manufacturing
(CIM) in 1990 has not been and will not be realized because of:
• Inability to measure financial performance of system solu-
tions
• Confusion between products and solutions businesses
• Failure to license solutions based on shared risk-shared
reward (SR2) performance relationships.
In the beginning. Chemical process systems engineering
for dynamic analysis and control was inaugurated in universities
and large operating companies like Shell, Esso, Mobil, DuPont,
Phillips, Texaco and Monsanto in the 1960s. Chemical process
operation was deemed the third arena of chemical engineering,
after product development and manufacturing plant design. Con-
trol systems engineering was created for mechanical, electrical,
aerospace, agricultural, chemical and business systems.1–29 Analog
instruments and early digital computers were used for feedback
and feedforward control of flow, temperature, pressure, level and
product qualities.
Advanced process control was developed and commercialized
for the HPI in the 1970s by several advanced control suppliers
using general-purpose computers with real-time Unix operating
systems connected to basic pneumatic, electric and new digital
controllers. Investments were initially justified on cost savings like
manpower reduction, which operators despised, or on the notion
that everybody else is doing it because computers are good so we
must keep up-“the faith theory.” Soon process yield and utility
credits were seen.
In the 1980s, CIM expanded to distributed control systems
(DCSs), multivariable control, online optimization, scheduling,
plantwide control and IT integration throughout the worldwide
HPI. Investments were justified by smoother operation that made
no direct money but allowed average targets to be moved some-
Demise and keys to
the rise of process control
Modeling the penalty for violating constraints as well as
modeling the credit for approaching them, and shared-risk
shared-reward business practices are the solutions
P. R. LATOUR, Clifftent Inc., Houston, Texas
N LITERATURE REVIEW
A host of papers have attempted to identify the reasons
for the demise of the automation business. A comprehensive
study of numerous publications indicates the confusion. Some
say it’s technology; some say it’s relationships. Practitioners
seek performance, suppliers promote results, customers com-
plain about invisible benefits. Kane provided insights from a
computer conference full of ideas but lacking sound financial
support to sustain quantified benefits.71, 72
Technology
Flaws. Many have cited technical flaws. Friedman pushes
better inferential measurements73–78 but has no way to quan-
tify the financial consequences and he fears the process control
industry has completely collapsed. Qualities were first commer-
cially inferred from simple measurements in 1971, when crude
unit side-draw TBP cutpoints were inferred from temperatures,
pressures, internal refluxes and steam rates.219–224 King decries
poor engineering practice and shows 14 ways to lose money
with improper property inferentials but does not quantify the
losses rigorously.79, 80 Smith has long proposed knowing how
the process works but never relates process operation to its
associated economics and profit generation.81, 82 Hill regularly
writes on the value of good operators but cannot quantify
their financial performance.83–87 A supplier’s survey88 reported
the biggest challenges: limited budget for integrating software
with business performance, 35%. (Budgets should never limit
compelling profit generation.)
Six Sigma management. Doble reports 13 Six Sigma myths,
confirming it has floundered due to lack of proper dynamic
financial performance measurement,89 as reported by Clif-
ford.90 Welch had the same difficulty.91–94 Stewart reports on
CEO Larry Carter’s use of up-to-date information to run Cisco,95
which could probably be standardized with clifftent.42
Limit setting. Hartmann’s refinery LP work clearly shows the
financial importance of setting constraint values properly,96 as
proposed in 1996.42, 45 Kalis has an excellent description of the
importance of knockout drum demisters to protect compres-
sors,97 a large profit opportunity for statistically optimal gas
velocity setting42, 45; Golden confirms.98
Continued
3. BONUSREPORT DEMISE/RISE OF PROCESS CONTROL
72
I MARCH 2006 HYDROCARBON PROCESSING
what in a more profitable steady-state direction.30–33 A major
DCS vendor’s ads featured King Cole surrounded by piles of gold.
The faith theory prevailed, but savvy management continued to
inquire: Please show me where the money comes from and how
much is net; we want secure, sustained profits.
At the peak. By 1990, CIM was poised to profoundly con-
tribute to profitable manufacture of clean fuels like reformulated
gasoline (RFG), enhancing refinery performance by $1/bbl crude
and refining plus downstream petrochemicals by $2/bbl crude.
The technology was known, experienced staff was affordable,
hardware was capable and improving, and economic drivers were
clear.34–37
Throughout the 1980s, universities were busy teaching process
control methods, developing algorithms, writing papers, present-
ing short courses and analyzing commercial multivariable control
algorithms.The National Petroleum Refiners Association (NPRA)
began separate annual process control conferences attracting
300 worldwide. The Instrument Society of America (ISA) had
large annual conferences and exhibits. The American Institute of
Chemical Engineers (AIChE) was active with papers and confer-
ences. Instrumentation suppliers were busy. Major HPI magazines
published articles on developments and accomplishments in every
issue. Articles invariably touted a method, algorithm, controller,
model, system, project or product that generated a payout in <12
months. Books were published. Control systems engineering was
recognized as the technology for profitably mitigating risk, reduc-
ing uncertainty, improving quality and satisfying customers.
Suppliers offered hardware, software, services, studies, projects,
experience, algorithms, models, databases, technology, instru-
ments, analyzers, control systems and a host of other components;
all products, on trust, without guarantees or refunds. Commercial
risk was not properly aligned with technical know-how. Customer
operating companies accepted all the risk for success without
proper knowledge; solution providers took no risk because they
really did not know how to measure the value of their offerings.
Investments were justified on simple, ad hoc, steady-state change
predictions in process performance allowed by smoother control.
(All processes are dynamic; steady-state is a mathematical figment
of human imaginations.) Users pushed project implementers to
leave to cut costs rather than entice them to stay to sustain profits.
Project implementers were anxious to leave to avoid maintenance
rather than stay to sustain profits. There were no performance
standards; confusion reigned; the faith theory prevailed.
Quality control gained visibility from Deming, Crosby, Juran28
and Peters. ISO 9000 quality procedures were inaugurated. Ford’s
Job1 was announced to compete with Japanese car quality. Quality
circles and Six Sigma were promoted. Arthur D. Little pioneered
hazardous operations (HAZOP) analysis. IT went commercial,
system and business integration was the key. CIM became reen-
gineering, then plantwide control, then value-added supply chain
management. They are all subsets of process control that generate
intangible benefits but suffered due to lack of a rigorous method
for quantifying financial value from improved dynamic perfor-
mance, i.e., reduced variance. Financial verification was impos-
sible; faith theory was victorious.
IT was described in Harvard Business Review and business
schools. Large systems engineering theories and nonlinear opti-
mization methods were published. Risk management was pro-
moted. The mantra was to apply good ideas and post-audit for
Lemmers shows the importance of limit setting for com-
pressor surge and stonewall99 without a method for setting
them optimally or quantifying the control system financial
value. Amrouche gives tank limit setting standards100 which
could be optimized for uncertainty and financial conse-
quences.42, 45
Safety
Risk management. A risk management feature101 lacks
any sound performance measure. Ghosh claims improved
critical condition management can add at least 5% to prof-
its102 but lacks the proper method to measure and prove this
claim. Mannan promotes the Mary Kay O’Conner Process
Safety Center,103 long handicapped by lack of a method
for connecting limit violation penalties to process credit
tradeoffs statistically and financially to quantify the value
of safety management, as provided by clifftent. Ayral pro-
motes critical situation management,104 but does not include
the power of clifftent risk management to avoid pitfalls to
financial success.
Abnormal situations. Some seek the link between process
operation and abnormal situation reliability management;
between process control and safety alarms. Two magazine
editors see the opportunity that clifftent resolves: Gonzalez
describes the reliability challenges and opportunities in refin-
ing105 and Rosenzweig describes the unsolved opportunity
for abnormal situation management in the chemical indus-
try.106 Alford struggles with the value of alarm management
using ad hoc alarm ranges107 that was superseded by clifftent
in 1996.42 Brown gives alarm management guidelines108 but
lacks a quantitative measure of financial merit. Hill describes
the importance of alarm management84 but does not quan-
tify its value. Grosdidier offers a path forward for DCS alarm
management,109 but does not quantify its financial value.
Goble offers a risk-reduction approach to manage the safety
life cycle,110 recognizing the need to properly connect to
financial value, as already solved.42 Nimmo’s alarm manage-
ment feature111 lacks any way to measure the financial value
of his proposals.
Plant maintenance. Many seek to connect process opera-
tion to equipment wear and tear; operating credits against
maintenance costs. Clifftent risk tradeoffs abound. FIATECH
reported on plant operations and maintenance information
needs and problems of financial justification.112
Relationships
Successful business partnerships are an HPI hallmark.
Engineering and construction (E&C). Valot has pleaded
for more value-oriented owner/contractor relationships with
properly aligned commercial risk and reward,113, 114 as pro-
vided by SR2 licensing of CIM solutions. Moore writes about
enterprise resource planning (ERP) maintenance contracting
with questions touching on value-added aligning of risk and
reward.115 Cunic shows the importance of performance-based
E&C contracting,116 claiming “key to successful performance
contracting depends on understanding (should add measur-
ing) the net effect, impact or benefit that a contracted scope
of work will have on business results long term.” Transmar
4. DEMISE/RISE OF PROCESS CONTROL BONUSREPORT
HYDROCARBON PROCESSING MARCH 2006
I 73
value—not to first seek quantifiable value and deploy what is
necessary to capture and sustain that value to maximize expected
value profit. With the Internet on the horizon, remote mainte-
nance was born.
Paradigm shift proposed. By 1990, the fragmented prod-
ucts/components process control business, armed with power-
ful technology and skilled implementers, was poised and ready
to mature into a performance-based solutions business. A few
recognized that the technology slogan and hype bubble could
not continue. They realized that failing to follow the scientific
method (measure results to confirm theories) leads to chaos and
failure.38 The question remained: how to measure the financial
performance of dynamic system improvements to prove the value
added and properly guide use, investments and maintenance?
The proposed new mission was to identify, capture and sustain
significant economic benefits for clients and suppliers from prop-
erly integrated CIM solutions.34–37, 39–50 Rather than continue to
offer to install products and projects that payout handsomely in
six months and generate large profits henceforth without main-
tenance and upgrades in the face of overwhelming evidence that
this approach invariably led to disappointment and failure, the
new proposal was for much more careful attention at the start to
process economics, clear measurement of process plant financial
performance improvement and the business requirements for
assembling technology solutions to make money for those who
accepted commercial risk. The HPI has had too many six-month
payoffs by intangible and transitory benefits.
Performance measure technology. CIM technology had fatal
flaws related to lack of a method for measuring the financial value
of improved dynamic performance, or reduced variance, until the
concept of clifftent was published in a seminal 1996 paper42 and
subsequently extended.43–45, 47–50 It provided the long-sought
method for constructing profit meters for each control variable
(CV) and key performance indicator (KPI). Control engineers
have worked excessively on reducing variance without being
able to quantify the value of such improvement. They wrongly
assumed the limit and target mean for CVs and KPIs are properly
given, or optimal, when they never are, and when the value of
setting them optimally is easy42, 43, 45 and just as rewarding as
variance reduction by all CIM, i.e., $1/bbl crude refined.
They failed to model the steady-state profit function for each
CV/KPI, which is invariably shaped like a tent, defining the ben-
efit tradeoff, often with a discontinuous cliff at the most profitable
limit point. They failed to appreciate all process performance
improvement is embodied in modifying the shape and position
of the distribution function of CVs and KPIs. That is all one can
do mechanically to change process performance (other than trivial
cost reductions that do not impair process performance). Proper
connection of the distribution function to the steady-state profit
tradeoff tent function for each CV/KPI provides the rigorous way
to measure financial benefit from variance reduction and resetting
targets and limits.This is rigorous risk management for maximum
expected profit rate. The consequences for modeling process
profit are profound and illustrate the disconnects that permeated
the CIM business for 40 years since 1965.
People wrongly assume reduced variance alone has no quan-
tifiable financial value. In fact, the 1996 discovery42, 45 showed
it was equivalent to simple conventional claims for moving the
new mean closer to a spec or limit by some arbitrary amount after
describes the perennial E&C industry contracting troubles
and calls for performance-based strategic alliances.117
CIM. Since CIM performance is easier to measure42–45 than
E&C performance, SR2 licensing is much easier for the CIM
solutions business. Cobb has published comments on the
demise of IT by accounting firms and suggests the need for
the right value proposition for sustained results.118, 119 Hill and
Walker see Dow collaboration as key to value chain opera-
tional excellence,120 while seeking a rigorous method for mea-
suring its financial contribution. Bullemer writes on the role
of the operator to push processes to their optimal limits and
seeks a rigorous method to benchmark the value of improved
performance,121 as reported in 1996.42, 45 Bullemer endorses
the Abnormal Situation Management Consortium’s highlights
that the plant operator’s role needs a new profit paradigm,122
realizing the need for a proper method for measuring finan-
cial performance. Mohrmann shows how to include the field
work force in the automation loop123 but needs a way to
quantify the financial value.
Practitioners
A few control engineers recognize the demise and have
published ideas to reinvigorate process control.
Quantify benefit. White noted the benefit problem and
offered an ad hoc statistical method to value information and
decisions,124, 125 which is handled rigorously by easier means.42,
45 Martin published his understanding of control benefits
with an ad hoc statistical approach126 that does not rigorously
incorporate economics.42, 45 Grosdidier offers seven tips for
APC project success and a value proposition for oil account-
ing, claiming $1.4 million/yr without proof127, 128 but excludes
financial performance and misstates the source of value of
APC (APC does not push constraints, it only allows others, like
clifftent, to attempt it). Grosdidier did utilize and reference
clifftent work to analyze blend giveaway economics.129
Measure pleas. Fiske frequently promotes the connec-
tion between IT and operations and shows process variability
causes underperformance130–133 without realizing his problem
is solvable.42, 45 Woll also promotes proper organizational
roles for performance131, 134–136 without a proper measure to
keep financial score. Mowat, Woertz and O’Malley confirm
the need to quantify the intangible benefits (soft stuff) to
create value.68 Beautyman assesses profitability of real-time
optimization (RTO) with pre- and post-audits137 but does
not provide the rigorous financial performance measure to
quantify profit creation. Pandit’s profitability of optimization
letter in response to Beautyman138 hints at a weakness of RTO
that emphasizes excessive model rigor for behavior inside the
constraints where the plant should not operate, but unrealistic
modeling at the constraints where it should operate, while
improperly setting the constraints—which was revealed in
1996.42 Pitt described the need for measuring financial value
for refinery supply chain management and human operators
well.139, 140 Powley described the need and requirements for
financial performance measure for MPC and KPIs very well.141
Lang describes the use of process KPIs but does not relate
them properly to financial value.142 Canney tries to explain
the dearth of benefit from 6,000 APC installations by claim-
5. BONUSREPORT DEMISE/RISE OF PROCESS CONTROL
74
I MARCH 2006 HYDROCARBON PROCESSING
variance was reduced. The 1996 discovery of how to integrate the
CV distribution to its associated profit function (shaped like a
clifftent) to give the profit hill vs. CV mean also gave the optimum
setpoint move size and corresponding profit gain, providing addi-
tional value at trivial cost. It proved the proper distance between
limit and mean is never six standard deviations or Six Sigma.
It showed how to set limits and targets properly to mitigate
risk. It transformed arbitrary limits for statistical process control
and alarm management into economic optimum limits. It showed
the weakness of rigorous online optimizers that were merely con-
straint corner pickers because they had no model of the physical
and financial consequences of breaking dependent CV constraints.
It showed that the benefit of process control cannot be properly
determined without the economic sensitivities and discontinui-
ties associated with each CV embodied in its clifftent function. It
showed the financial value of better-performing solution compo-
nents: control valves, analyzers, instruments, models, algorithms,
tuners, databases, computers and maintainers.
Once engineers and managers certify the five economic sen-
sitivity parameters, clifftent gives operators a new paradigm for
running plants by optimizing risk management: forecast CV/KPI
near-term variance. That’s it, the basic human input.
Process control benefits can be double traditional claims, but
they must be visible, tangible, current, accurate and accepted.
Clifftent connects the statistical properties of dynamic systems to
financial value, like string theory connects quantum mechanics
to relativity,38 but with more immediate benefit to people.52, 53 It
optimizes tradeoffs under uncertainty, as basic as setting the speed
of your car near the posted limit. It revealed the need to model
the penalty for violating limits to be as important as modeling the
credit for approaching them. Many have sought this mathematical
modeling method to reconcile and optimize clifftent tradeoffs.54,
55 The only significant performance claim to quantify financial
benefit for control/IT is CV/KPI variance reduction.
Koppel’s elegant, comprehensive ISBEN approach to quantify
information system benefits from all associated business activities
is particularly noteworthy.56 Koppel has long advocated greater
attention to proper performance metrics for control and IT sys-
tems.11, 14
Lack of proper performance measurement cannot be over-
emphasized.The situation is like 100 million football fans ready to
view the Super Bowl kickoff when one team claims a touchdown
is worth five points and the other says six. As they argue back and
forth, the fans say they don’t particularly care whether it’s five or
six, but they really care that the opponents agree on one value and
agree the team with the most points fairly scored after 60 minutes
is the game winner. The Olympics are viable when all competitors
and viewers understand and agree on the performance scoring
measures. Without that, there is no reason to participate.
As long as CIM practitioners fail to adopt the proper financial
performance measure standard to maximize expected value of net
present value (NPV) profit over a long term, say 30 years, fairly
discounted, they remain unable to prove the value of their work
and solutions to properly serve their customers and themselves.
As long as process control publications continue to describe some
method or tool and claim <12 month payout henceforth and
forever, the CIM demise will continue henceforth and forever.
Financial analysis of CIM solutions should be like a 30-year home
mortgage or a lifetime annuity: economic value added (EVA) with
realization probabilities.
ing 15 statements are myths, attempting to refute them and
summarizing with “truth.”143 Actually only seven were real
myths; Canney refutes six. His three claimed truths illustrate
the reason for the demise.
Suppliers
Results. Many solution providers promote performance
and results but cannot license based on their rightful per-
centage because they cannot measure their solution financial
value-added properly. One database software supplier has
an IT monitor for network performance and enterprise per-
formance management144–146 but investigation revealed it
does not relate physical statistics to profit.42, 45 A DCS vendor
claims its “solution” or product and its KPI manager improve
plant profitability, promising quick, no-risk payoffs,147–149
without any rigorous method for proving such claims. A
large system supplier recognizes the performance oppor-
tunity with its “Prove It” ads 150–152 but might gain with
a rigorous financial measure and solutions performance
licensing. (If they could really prove it with an unambiguous,
rigorous financial measure of their solutions’ performance,
they would undoubtedly offer it privately to selected clients
rather than publicly advertising that their customers want
them to prove it.)
Confusion. Another DCS vendor mixes solutions and prod-
uct components,153–156 with no measure of financial merit.
An experienced control engineer offers fast operator advi-
sor software, but has no method to quantify its financial
value.157 A consulting firm often advertises Optimum Plant
Performance.158, 159 A supplier offers free public literature on
performance optimization benefits rather than private profit
sharing sustained solutions.160 A large system vendor offers a
results-driven automation World Conference & Exhibition161
without a rigorous method for measuring the financial value
of improved dynamic solutions. It also offers software to run
plants smarter162 without quantifying financial gain.
A compressor controls company has promoted the benefit
of compressor controls with proper attention to limit and tar-
get setting but lacks a rigorous way to quantify the important
financial value.163, 164 A software firm promotes MPC control-
ler performance141, 165, 166 but does not claim rigorous financial
value. A large CIM solutions, products and control provider
offers fast polymer-grade changes for six-month paybacks167
with no method to properly quantify their financial value.
Further, they broadly claim increasing ROI rather than EVA for
customers168 without offering a rigorous way to quantify and
sustain benefits, profits or ROI, when its technology is pow-
erful enough to allow it to offer a risk-free, zero-cost annu-
ity and infinite (hence, meaningless) ROI to their customers.
(Getting the scorekeeping right is important.) Another report
describes the widespread confusion about ROI as the proper
performance measure for e-business.169
Strategic offers. The major IT platform vendor has long
struggled with measuring the financial value of its supply
chain software platform.170, 171 An expanded control solution
that boosts production performance is actually two software
products that do noble things that are not financially quanti-
fied.172, 173 An HPI operating company solutions provider offers
6. DEMISE/RISE OF PROCESS CONTROL BONUSREPORT
HYDROCARBON PROCESSING MARCH 2006
I 75
Products vs. solutions. Process control offers confuse the
normal commercial distinction between products and solutions;
the difference is profound. Know your customer; know your offer.
Align commercial risk with know-how. Process control and IT
businesses are infected with a fatal disease of confused mixing of
products and solutions businesses.
Products, tools, components, software, algorithms, models,
databases, platforms, valves, instruments, projects and services
should only be sold to customers seeking product components
(that they presumably will integrate into sustainable profit-gen-
erating solutions). Products are sold on features, capabilities and
cost; often competitively bid for low price. The customer takes
the risk of generating value from them because he or she has the
know-how to do so. Products are sold in grocery stores, lumber
yards, pharmacies, bookstores and Websites.
CIM installation solutions that generate sustaining value-
added are sold to customers seeking solutions. Solutions combine
hardware, software, technology and appropriate people to gener-
ate sustainable process profits for the plant customer and supplier.
Solutions are sustained by performance, results and value added;
never competitively bid for low cost. The supplier takes the risk
of generating value because it has the know-how. Solutions are
offered by restaurants, realtors, physicians and colleges.
Never sell products to customers seeking solutions; it’s a com-
mon disconnect. Never sell solutions to customers seeking prod-
ucts; it’s a common disconnect. Never buy products based on
sustained financial performance; it’s a disconnect. Never buy
solutions on low-cost competitive bidding; it’s a disconnect.
(People never select a computer, college, home, suit, car, physi-
cian, attorney, vacation, restaurant or much of anything on low-
cost competitive bid. They buy on value; cost is only one of many
considerations.)
Operating company customers want CIM solutions that gen-
erate maximum expected NPV profit streams sustained over long
periods, like 30 years. They do not want maximum benefits that
may be costly, minimum costs that may have no benefit, six-month
payouts that are not sustained. They do not want to risk capital or
spend money. They really don’t care how the solution works, just
how much money it makes.They want clear, large, sustained, easy,
legal, ethical, no-risk profits.They want large variable annuities, for
free. CIM has offered this potential since 1990.
Licensing performance solutions. The CIM business failed
to mature to a sound solutions business, where experienced sup-
pliers knew enough about the financial value of their numerous
installations integrated into operating plants and how to identify,
capture and sustain their value. Had they done so in 1990 they
would have evolved naturally to SR2 licensing arrangements that
endure. Their sales costs would have evaporated.43, 44
Since profit-oriented CIM investments are so attractive, sup-
pliers could have easily offered free net revenue streams or free
variable annuities from $1/bbl profits with expected NPV (30
yr, 8%) = $875 million for a 200-Mbpd refinery. This provides
comprehensive solution suppliers about 25% of that amount.43, 44
Experience established the existence of an optimum benefit split
between the operating company customer and its CIM solution
supplier to sustain performance over say 30 years to realize such
value.43, 44 This explains why ROI, touted as the performance
measure by one supplier for years,168 becomes meaningless; invest-
ment is zero, ROI is infinite. It’s the size of the zero-risk profit
stream EVA that matters. No-risk SR2 offers are most appropriate
services and technology to improve margins by squeezing to
make every last drop count174 without a sound method for
measuring and proving financial value. A chemical operating
company global service provider offers simulation tools, per-
formance monitoring, manufacturing economics and supply
chain optimization175 without a rigorous financial perfor-
mance method for sustaining solutions. Another chemical
operating company offers dynamic benchmarking of plant
performance in physical terms176 without standardizing on a
rigorous method for financial value.
A tank terminal automation firm offers flexible solutions
to optimize operation177 without a way to measure financial
value. A controller tuning expert firm promotes the impor-
tance of proper loop tuning178, 179 but suffers from inability
to connect reduced variance to money.42, 45 A major computer
firm recommends “the HPI harvest a return on IT investments
by managing risk in terms of individual elements of risk, and
the combined business and operating risk to strike the best
balance between optimization and predictable production
of products to achieve refining excellence,”180 which is easily
done with clifftent on every CV and KPI.42, 45
An accounting method is offered to define a plant’s true
profit potential, generating 20% to 40% profit increases,181
but it is not clear if process behavior and statistical risk man-
agement of dynamic performance are covered. (Accounting
is designed to measure profit after-the-fact, not forecast,
manage and optimize it in real time.) ISA has offered a train-
ing course that includes justifying automation projects182 that
lacks a proper method for measuring financial performance
of automation and control systems.
Poor benefits. Since the 1970s, many authors reported
interesting technical successes with weak financial gains.
Recent articles continue the practice. Rotava reports an inter-
esting application of MVC and RTO (commercialized in the
early 1980s) on a South American crude unit with no discus-
sion on value.183 McFarlane describes improved crude unit
optimization156 with benefits from fast project completion
in six months but no proven, quantified process economic
benefits. Bonavita offers a step-by-step approach to APC184
that neglects proper scorekeeping at the outset and sustained
financial performance thereafter. Chang offers a well-known
graphic display wheel to capture process control benefits but
cannot quantify the value of his contribution.185 Barsamian
has promoted inline blending analyzers and control without
any way to quantify their financial merit.186 Sanz & Papon
tout traditional MVC to a batch reactor but cannot determine
its value, relying on faith theory.187 Mandal does a nice job
describing improved desalter and level control but cannot
quantify their value.188, 189 Galante describes a molecule man-
agement technique to improve real-time, process unit optimi-
zation tools with no method for quantifying its value.190 Kelly
has published extensively on IT techniques like reconciliation,
scheduling and models without a sound method for quantify-
ing financial merit.191–195
Moore relates process control to environmental impacts
and H2 management but cannot quantify the financial
value.196, 197 Sivaraman recognizes the critical nature of proper
control limit setting for loss control but his statistical method
7. BONUSREPORT DEMISE/RISE OF PROCESS CONTROL
76
I MARCH 2006 HYDROCARBON PROCESSING
for the doubting, skeptical, risk-adverse, inexperienced operat-
ing companies. Sharing a percentage, a piece of the action, is an
old, proven way to higher profitability for both parties. It affects
behavior in meaningful ways. Think about the Super Bowl and
Olympic games. Refinery control engineers who add value by
specifying clifftent input factors should earn 2% to 3%. Supplier
employees should earn 3% to 4%. Researchers should earn 3%.
SR2 licensing eliminates the need for the solution-supplier
sales staff. Rather, supplier executives manage and expand each
client SR2 relationship as his or her profit center, integrating and
deploying appropriate products to sustain the engineered solution.
Advertising and publications are useful for product offers, not
sustaining CIM solutions.
SR2 licensing eliminates the need for operating company tech-
nology-product appraisal staff. Rather, operating company execu-
tives focus on economic factors like margins, differential values and
consequences for breaking limits as input to clifftent for optimizing
KPIs.They forecast risk (in terms of variance based on historic vari-
ance) to optimize sensitive tradeoffs, operate plants as profit centers
with CIM solutions and are delighted to share meaningful benefits
to their risk-taking solution providers because they understand
sustaining success depends on fair, mutual profit and risk sharing.
No interest. Performance measurement and solution licensing
know-how was offered to all HPI CIM solution providers and
major operating companies—privately and publicly—during
the early 1990s,34–37, 39–50 but the obsolete faith theory products
features business paradigm prevailed.
Situation today. What happened since 1990? What is the
situation in 2006? What’s next?
Academia no longer teaches, researches or publishes chemical
process control or CIM. Process control and instrument engineers
at operating companies and suppliers have left their profession.57
Association conferences like NPRA, ISA, AIChE and JACC have
declined dramatically in content, attendance and interest. The
NPRA plant automation conference declined from over 300
attendees in the 1980s to fewer than 100 in September 2004
and was combined with process engineering in September 2005.
Literature has declined. Few books are written. Magazine articles
are repetitious and unconvincing, still superficially touting meth-
ods with <12 month payouts. Quillin wrote about some “critical
issues” for CIM in the HPI58 but repeated old hoopla and cannot
prove the magnitude of any financial value from his assertions.
Suppliers are offering the same familiar tools and products
while creating insufficient profit for their shareholders and facing
declining revenues, layoffs and consolidations in shrinking mar-
kets. They struggle with ill-conceived mergers and acquisitions.
Suppliers are not very profitable. One stock with no dividends
should have grown from $40/share in July 1997 to 40(1.3)**8 =
$326/share by June 2005, yet it has languished below $10/share
since July 2002 with weak competition; a massive destruction of
shareholder wealth. (Analysts attribute this to the sum of prof-
its over a decade <0.) Most CIM suppliers have failed to create
shareholder wealth. Recently, a Western European oil movements
CIM specialist since 1980 disclosed it lost a contract for a Viet-
namese refinery to a new group in Eastern Europe which was
under-bidding engineering services at $25/hour. This is a natural
consequence of failure to offer assured performance with no risk.
At a time when blending for boutique RFG and low-sulfur diesel
(LSD) provides large incentive to get it right, this is a tragedy.
does not connect to economics.198 A control systems supplier
offers polymer process advanced control and optimization
after acquiring an advanced control company and its powerful
controller, but has no way to determine its financial value.199
Wilson reports statistical control of an FCC with classic statis-
tical quality control (SQC) limits because he does not have a
rigorous way to convert dynamic improvement into money.200
Mathur features superfractionator MVC without plant tests
and significant CV variance reduction201 but is not able to
convert his accomplishment properly into dollar profit. Martín
offers a new control scheme for an SRU, reducing standard
deviation by five and sulfur emissions approximately 250 mt/
y,202 describing the air/gas clifftent tradeoff without properly
determining the value of standard deviation reduction or
optimally setting the setpoint.42, 45
Sharpe justifies tools and services on cost reduction203
rather than rigorous process performance improvement, which
is an order of magnitude larger but impossible to prove if you
don’t know how. Cheng offers another algorithm for distilla-
tion control204 without showing any superior profit genera-
tion. Sayyar-Rodsari reports on MPC for nonlinear processes205
without showing any superior profit generation. Deshpande
claims turbocharging a constrained model predictive control-
ler with fuzzy logic allows application to nonlinear systems,206
but cannot quantify the financial merit of his idea.
Novak writes on SCADA’s support of business processes
and supply chains,207 without quantifying financial value.
Kern implements expert online operator advisors,208 without
quantifying its profit generation. Valleur describes optimiz-
ing refinery scheduling comprehensively but omits any mea-
sure of financial performance; benefits are listed as words.209
Gilbert writes on implementing an environmental, health
and safety management information system210 with ten tips,
none of which include a measure of financial performance.
Karagoz claims a breakthrough in polymer control improves
the business cycle211 but does not rigorously convert statisti-
cal improvement to profit. Hall extols the importance of MVC
plant testing and that recognized big money comes from
pushing constraints properly,212 but he cannot quantify the
value of his proposals.
Singh describes business-to-manufacturing integration
using XML throughout the supply chain,213 which can col-
lect data input to KPIs.42 Moore offers several ways to cap-
ture value from supply chain management and ERP,214, 215
which require a rigorous method to determine financial
performance.42, 45 Catalyst monitoring software216 would
be strengthened if it incorporated a rigorous method for
quantifying the financial value of dynamic performance and
optimizing tradeoffs.42, 45
Sim claims optimizing asset utilization through process
engineering improves ROC up to 4%217 with no way to prove
it without a rigorous method relating risk abatement to
profit.42, 45 Sim also reports on advanced cubic equations of
state218 but offers no way for his customers to determine their
worth or value over his price; clifftent tradeoffs to optimize
limits and setpoints require process models and can quantify
comparisons with less rigorous approaches to guide when
model fidelity is sufficient.42, 45 HP
8. DEMISE/RISE OF PROCESS CONTROL BONUSREPORT
Suppliers of alarm management, abnormal situation manage-
ment, HAZOP analysis and safety shutdown still struggle with
financial performance measurement of their systems because
they do not connect to process operation control. Plants risk
unplanned atmospheric emissions and catastrophes like BP’sTexas
City isomerization unit raffinate splitter explosion in 2005.59
Operating companies continue to complain about process
control performance—the inability to see tangible benefits.
They are disappointed; they have lost interest. Control engineers
blame management for lack of vision and budgets; management
still says show me the money first. Operating limit violations
cause unplanned damage like Environmental Protection Agency
(EPA) settlements60: Valero $705 million, Motiva $550 mil-
lion and ConocoPhillips $525 million. Company CEO William
Wise reported El Paso lost a suit charging they withheld natural
gas pipeline capacity from California, raising prices, because
“EPNG did not consistently operate at or near its maximum
allowable operating pressure on a continuous basis.”61–63 Had
EPNG understood and deployed the principles of clifftent,42
they would have a mathematically sound legal defense. The US
Supreme Court ruled that economic factors could not be used by
the EPA in setting air quality standards because it “could simply
complicate the procedure without improving it.”51, 64–66 Justices
Scalia, Ginsberg, Breyer, Souter and Rehnquist were seeking a
sound basis for economically optimizing limits and targets, but
the American Chemistry Council, EPA and Solicitor General were
unaware that clifftent provided a simple mathematical method to
do it. The relief valve sizing standards67 do not properly optimize
risk tradeoffs.
Refinery and petrochemical margins reached historic highs
in August 2005; a golden age for HPI profits has arrived.68 ARC
forecast the process industries automation market in 2003 to
grow 4.7% to $58 billion and fieldbus adoption was growing
rapidly.69, 70
President G.W. Bush and the Saudi Oil Minister have publicly
agreed fuel availability in the US will be limited by oil refinery
capacity rather than producing field capacity. If so, refinery mar-
gins will grow. Then proper determination and setting of equip-
ment limits and targets as well as product quality limits and targets
with clifftent becomes the main operating challenge for produc-
tion and profit. The CIM benefit potential in 1990 of $1–$2/bbl
crude has undoubtedly increased to >$3/bbl by July 2005. (See
the literature review sidebars for insights into the reasons for the
demise of the automation business and the confusion.)
Outlook. While control and modeling technology is sound,
instruments work and computers are fast and cheap, the whole
computer application to manufacturing field, CIM, suffers from
failure to adopt a definitive, comprehensive, rigorous, standard
method42 for measuring the financial value of dynamic systems
performance.
Once solution suppliers and their customers agree on that,
solutions can be offered based on proper SR2 profit sharing.43,44
In most cases, the cost of generating compelling value is so low
the supplier can offer selected plant clients a variable annuity,
for free. Once clifftent optimizing modules and CV/KPI profit
meters are standard components in commercial databases, every
CV and KPI setpoint will be optimized based on forecast vari-
ance, and the financial consequences of variance changes will
be quantified.
Process control and CIM businesses are in a long decline,
failing to realize promised benefits, because they do not properly
measure the financial value of dynamic performance of installed
solutions, commercially confuse products and solutions, and
remain unable to pursue performance-based licensing of sustain-
ing solutions.
With so much time lost, so many mistakes made, such wide-
spread confusion, so many competent and experienced con-
trol engineers retired or gone, so few newcomers and so much
damaged infrastructure, the demise of process control and CIM
appears destined to continue. Is anybody delighted?
HPI profit increase potential exceeding $2–$3/bbl crude refined
85 million bpd worldwide will remain unrealized until the CIM
demise is reversed.The main lesson is never invest or embark on an
automation activity without a rigorous measure of financial value
from improved dynamic system performance. Never. Don’t gamble
on a game that does not have a clear method of scoring either. Don’t
neglect the scientific method; it works for business too. Ignoring
these is a recipe for failure, perhaps disaster. HP
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Hydrocarbon Processing, May04, p. 19.
133 Fiske, T., “Real-time performance management unlocks hidden value in assets,”
Hydrocarbon Processing, Aug03, p. 15.
134 Woll, D., “Time to rethink process plant roles and responsibilities,” Hydrocarbon
Processing, Sep04, pp. 15-16.
135 Woll, D., “Increased performance dictates more effective plant human assets,”
Hydrocarbon Processing, Apr04, pp. 17-18.
136 Woll, D., “Effective operations management,” Hydrocarbon Processing, Sep02,
pp. 17-18.
137 Beautyman, A. C., “Assessing profitability of real-time optimization,”
Hydrocarbon Processing, Jun04, pp. 39-42.
138 Pandit, H., “Profitability of process optimization,” letter to the editor,
Hydrocarbon Processing, Sep04, p. 18.
139 Pitt, R., “The intelligent refinery—or is it?” Hydrocarbon Processing, Dec03, p.
11.
140 Pitt, R., “IT makes further headway into the refinery,” Hydrocarbon Processing,
Jun03, p. 17.
141 Powley, G., “Performance visibility and the road to sustainable profitability,”
Hydrocarbon Processing, Dec03, p. 96.
142 Lang, L, and Gerry, J., “Universal key performance indicators for process
plants,” Hydrocarbon Processing, Jun05, pp. 83-85.
143 Canney, W. M., “Are you getting the full benefits from your advanced process
control systems?,” Hydrocarbon Processing, Jun05, pp. 55-58.
144 OSIsoft offer, “Real-time insights into operational metrics,” Hydrocarbon
Processing, Apr03, pp. 29-30.
145 OSIsoft offer, “Optimize inventory management,” Hydrocarbon Processing,
Dec02, p. 89.
146 Kennedy, J. P., “Executive interface for the process industry,” Petroleum
Technology Quarterly, Summer 02, pp. 113-117.
147 Honeywell offer, “Comprehensive simulation solution for processing plants,”
Hydrocarbon Processing, May05, p. 98.
148 Honeywell ad, “Honeywell automation quickly pays for itself,” Hydrocarbon
Processing, Sep03, p. 133; Hydrocarbon Processing, Aug03, pp. 2, 30-31.
149 Honeywell offer, “KPI Manager,” Gulf Publishing Company Software Reference,
Fall 03, p. 10.
150 Emerson ad, “Prove it,” Hydrocarbon Processing, Oct04, p. 48 and Hydrocarbon
Processing, Sep03, p. 21.
151 Emerson offer, “Model predictive control software application,” Hydrocarbon
Processing, Oct03, p. 105.
152 Emerson ad, “Prove it,” Petroleum Technology Quarterly, Summer 04, p.
68.
153 Jackson, K. M., “Invensys solution components,” Hydrocarbon Processing, Jan05,
p. 31.
154 SimSci-Esscor offer, “Improved advanced process control solution,” Hydrocarbon
Processing, Jan05, p. 88.
155 Invensys ad, “ArchestrA technology,” Hydrocarbon Processing, Sep03, pp. 8-9.
156 Ranganathan, S., A. Offerman, J. Cijntje, R. McFarlane, V. Lough, “Improved
optimization of a refinery crude unit,” Petroleum Technology Quarterly, Spring
2003, pp. 59-67.
157 Cutler Tech ad, “Operator Advisor,” Hydrocarbon Processing, Apr05, p. 67.
158 KBC ad, “Optimum Plant Performance,” Hydrocarbon Processing, Jun05, p. 8.
159 HP/KBC poster, “2005 Refining Advanced Process Control—Profit. Ability,”
Hydrocarbon Processing, Jan05.
160 Performance Plus offer, “Performance optimization services,” Hydrocarbon
Processing, Mar05, p. 85.
161 ABB ad, “Results-Driven Automation,” Hydrocarbon Processing, Feb05, p. 71.
162 ABB offer, “Data Acquisition and Analysis Software,” Chemical Engineering
Progress, Feb03, p. 53.
163 CCC offer, “Control system to increase olefins production,” Hydrocarbon
Processing, Dec04, p. 25.
164 CCC ads, “Turbomachinery Control Profit Enhancement,” Hydrocarbon
Processing, Aug03, pp. 29, 31.
165 Matrikon offer, “Operational excellence in controller performance,” Hydrocarbon
Processing, Apr04, p. 32.
166 Matrikon offer, “Software solution purchased,” Hydrocarbon Processing, Aug03,
p. 91.
167 AspenTech offer, “Resin Producers’ New Ally in Fast Grade-Change Transitions,”
Chemical Engineering Progress, Aug03, p. 10.
168 AspenTech ad, “ROI,” Hydrocarbon Processing, Apr04, p. 55 and Mar04, p.
20.
169 Aberdeen Group Ad Section. “Growing Technology ROI,” Fortune, 24Nov03,
pp. S1-18.
170 SAP ad, “If we can’t afford the solution, then it’s not a solution,” Fortune,
24Nov03, p. S7.
171 SAP offer, “Adaptive supply chain network solution,” Hydrocarbon Processing,
Aug03, p. 97.
172 Pavilion offer, “Expanded control solution boosts production performance,”
Hydrocarbon Processing, Jan04, p. 83.
173 Pavilion offer, “Pavilion Technologies Acquires Business Threads,” Chemical
Engineering Progress, Feb03, p. 23.
174 Shell Global Solutions ad, “Squeeze. Make every drop count,” Petroleum
Technology Quarterly, Autumn 03, p. 87.
175 Bayer offer, “New company transforms HPI ideas into reality,” Hydrocarbon
Processing, Jul03, p. 29.
176 DuPont offer, “Dynamic benchmarking of plant performance,” Hydrocarbon
Processing, Mar03, pp. 28-29.
177 Enraf ad, “Terminal Automation solutions,” Petroleum Technology Quarterly,
Autumn 03, p. 88.
178 ExperTune offer, “Process control consultant accessible in a box,” Hydrocarbon
Processing, Dec03, p. 25.
179 ExperTune offer, “Loop Performance Monitor Mines Knowledge From Data
Historians,” Chemical Engineering Progress, Jun03, p. 32.
