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The Road Less Traveled By: Adventures in Process Systems Engineering
2009 Computing in Chemical Engineering Award Lecture
Venkat VenkatasubramanianLaboratory for Intelligent Process Systems
Purdue UniversityWest Lafayette, IN, USA
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Acknowledgements: Ph. D. StudentsDr. Steven H. Rich (Wall Street)Dr. Ramaswamy Vaidyanathan (BP)Dr. Surya Kavuri (BP)Dr. King Chan (Wall Street)Prof. Atsushi Aoyama (Tokyo Inst Tech)Prof. Raghu Rengaswamy (Texas Tech)Dr. R. Vaidhyanathan(ExxonMobil)Dr. Dinkar Mylaraswamy (Honeywell)Prof. Dongil Shin (Myongji University)Prof. Raj Srinivasan (Natl U. Singapore)Dr. Hiranya Vedam (Singapore)Dr. Anantha Sundaram (ExxonMobil)Dr. Shankar Viswanathan (ZS)Dr. Sourabh Dash (ExxonMobil)Dr. Prasenjeet Ghosh (ExxonMobil)
Dr. Yuanjie Huang (ExxonMobil)Dr. Chunhua Zhao (Bayer)Dr. Santhoj Katare (Ford)Dr. Fangping Mu (Los Alamos)Dr. Mano Ram Maurya (UCSD)Dr. Priyan Patkar (ZS Associates)Dr. Shuo-Huan Hsu (OSI Soft)Dr. Ankur Jain (United)Dr. Sridhar Maddipatti (Fair Isaac)Dr. Shivani Syal (ExxonMobil)Dr. Bala Krishnamurthy (Amazon)Dr. Leaelaf Hailemariam (Dow)Dr. Arun Giridhar (Purdue)Dr. Pradeep Suresh (Dow)Dr. Pavankumar Akisetti (Intel)
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Acknowledgements
Former M.S. StudentsMargaret Janusz (Eli Lilly)Prof. Ioannis Androulakis (Rutgers)Kishore Kanakamedala(Aspen)Ramachandra SrinivasAtul Mohindra (Aspen)Thukaram KatareAyush GoyalMichelle Chaffee (Purdue)
Current Grad StudentsSanket Patil (IIIT, Bangalore)Intan Hamdan (Purdue)Aviral Shukla (Purdue)Maria Elisa Luque (Purdue)Prasad Raghavendra (Purdue)
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Acknowledgements
Post-doctoral Researchers
Prof. Yoshio Yamamoto (Tokai Univ., Japan)Prof. Mani Bhushan (IIT-Mumbai)Dr. Kris Villez (Purdue)Dr. Girish Joglekar (Purdue)Dr. Tanu Malik (Purdue)
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AcknowledgementsPurdue ColleaguesRex Reklaitis
Rakesh AgrawalGary BlauJim CaruthersNick DelgassFrank Doyle (UCSB)Jay Lee (GATech)Jim LitsterJoe Pekny
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Acknowledgements
Senior Colleagues
Larry BieglerTom EdgarChristos GeorgakisIgnacio GrossmannDavid HimmelblauManfred MorariGary PowersRoger W. H. SargentWarren SeiderJeff SiirolaGeorge StephanopoulosArt Westerberg
Contemporaries
Rene Banares-AlcantaraChris FloudasRafiqul GaniStratos PistikopoulosNick SahinidisNilay Shah
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AcknowledgementsDedicate this award to my Physics Lecturer
Mr. K. C. E. DorairajTaught me Physics in my freshman year
Mr. Dorairaj was an inspiring teacher Showed me that thinking about problems in physics can be a lot of funI decided then that I wanted to be a researcher
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Robert Frost: The Road Not TakenTwo roads diverged in a yellow wood, And sorry I could not travel both And be one traveler, long I stood And looked down one as far as I could To where it bent in the undergrowth;
Then took the other, as just as fair, And having perhaps the better claim, Because it was grassy and wanted wear; Though as for that the passing there Had worn them really about the same,
And both that morning equally lay In leaves no step had trodden black. Oh, I kept the first for another day! Yet knowing how way leads on to way, I doubted if I should ever come back.
I shall be telling this with a sigh Somewhere ages and ages hence: Two roads diverged in a wood, and I — I took the one less traveled by, And that has made all the difference.
Ithaca (June 1983)
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Vanderbilt and CornellVanderbilt University
M. S. in Theoretical Physics
Cornell UniversityAdvisor: Keith GubbinsThesis: Statistical Mechanics of Polar Fluids
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Road Less Travelled ByBecame interested in two questions at Cornell
How does the brain perform reasoning? What would the statistical mechanics of “reasoning”or “intelligent” systems be like?
Post-doc in AI at Carnegie Mellon in the Computer Science DepartmentArtificial Intelligence Models and Methods for Process Systems Engineering Problems
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Einstein’s Career Advice
“If you are sure about your ideas, then get a job as a light house keeper. It will give you a lot of free time to develop your ideas.”“If you are not so sure, then become a teacher – then even if your ideas don’t work out, you’d would at least have the satisfaction of contributing something useful to the society by teaching students.”
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Road Less Travelled ByInterested in conceptually “messy” problems
Problems that have not been paid much attention to due to their “messiness”
Mathematically ill-posed or ill-structuredNeeding Conceptual Clarity
Fault Diagnosis and Process Safety Quite different in character from design, control and optimization problems that have dominated the systems area.
Abnormal Events Management
Abnormal events are deviations in process behavior from normal operating regime
Safety problemsEnvironmental concernsQuality problems and Economic losses
Why do abnormal situations occur?Human errors Equipment degradation and failures
This is really a Process Control Problem
Academic View of Process Control
•x= f (x,u)y=h(x,u)
c(s) g(s)
h(s)
A → B
L[f(t)]≡−f (s)= f(t) −ste0
∞
∫ dt
Operator’s View of Process Control
A Day in the Life of a Plant Operator
Operator’s View of Process ControlPump A pumping oil has tripped - Cause UnknownYou switch to Pump B. That also trips - Cause UnknownSoon hundreds of alarms are going off – Cause(s) UnknownWith in minutes you have an explosion and a fire. Two people are killed and a few hurt at this point.It is 10:00 in the nightThe plant manager is in Aberdeen, Scotland, and not availableYou are on top of an off-shore oil platform in the middle of the North Sea
You are the Shift Supervisor: What do you do?
Process Safety is a Major Concern
Piper Alpha Disaster, Occidental Petroleum Scotland, 1988
Off-shore oil platform explosion164 people killed$2 Billion in losses
Union Carbide, Bhopal, India, 1984
MIC release into atmosphere
3000-10,000 people killed
100,000 injured
$0.5-1.0 Billion in losses
Process Operations Pyramid
Incr
easi
ng T
imef
ram
e
PROCESS
Regulatory control
Supervisory control
Planning
Monitoring & Diagnosis
Data acquisition
Area of Research FocusIntelligent Control Layer
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Opportunities for Methodological Contributions
DiagnosticMethods
Structural
Functional
Causal Models
AbstractionHierarchy
Fault Trees
Digraphs
Quantitative Qualitative
EKF
ParitySpace
Observers
QualitativePhysics
Process History Based
Qualitative Quantitative
Expert systems
QTA Statistical
StatisticalClassifiers
PCA/PLS
Neural Networks
Model-Based
Venkat Venkatasubramanian
Molecular Products DesignGiven a set of desired performance specifications, how does one rationally and efficiently identify the optimal product structures and formulations?$200+ Billion/yr industry: Major Opportunity for ChEs
Areas of ApplicationEngineering Materials
Polymer CompositesSolventsBlendsPaints and VarnishesRubber CompoundsCatalysts
PharmaceuticalsDrug Design
Agricultural ChemicalsPesticidesInsecticides
Zeolite!!?!?
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Pharmaceutical Product Development and Engineering
• Two ProductsDrugsDocuments
Preliminary product recipe
Drug is converted into ParticlesDrug Synthesis
Raw Chemicals
Formulation
Process Development
Preliminary process recipe
Scale/up -Tech Transfer
Adjusted process recipe
Manufacturing
A Delayed Product
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Drinking from a Fire Hose
– Managing Enormous amounts of Data, Information, Knowledge
Data Rich, but Knowledge Poor
010001001001111001000100101110000100011100100101010010001111100010001001000010001001010110001010000101010101001011010010010010010010010001001001001100000101001101010101011101111010010001110000001010111110101010101010
Venkat Venkatasubramanian, Plenary Lecture,Chemical Process Control 7, Canada, Jan 2006 23
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Data, Information, and KnowledgeData
What’s going on?Raw, does not inform much
InformationHow are the variables related?
Correlations and relationshipsKnowledge
Why are they related?Develop Mechanistic understandingFirst-Principles Based Math ModelsHeuristics
Tower of Babel of Data, Information and Models
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Data, Information, Knowledge, InsightRetrograde Mars
Newton’sLawof Gravity
Isaac Newton: Mechanistic Knowledge
Johannes Kepler: Correlations
Albert Einstein: General Theory of RelativityInsight Gravity as Space Time Curvature
Tycho Brahe
Product vs Process Design in ChEProduct design is where process design was about 30 years ago
Heuristic, Trial and errorLacking a formal conceptual framework for optimal decision making
Molecular level understanding very much essential
Need Molecular Physics, Chemistry, BiologyProcess design is largely at the macroscopic level
Quantum Mechanics, Statistical MechanicsDensity Functional Theory and ab initio calculations
Great opportunity for PSE
Need a New ParadigmHow do you get the
Right Information and Knowledge to the Right People at the Right Time in the Right Format, so that they can make the Right Decision
“Right Stuff”Cyberinfrastructure and Informatics
Ontology-based Models of Knowledge
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What is an Ontology?Originated in Philosophy: Study of ExistenceComputer Science and Artificial Intelligence
Formal specification of Concepts and RelationshipsKnowledge representation in AI
Logic, Semantic Networks, Frames, Objects, OntologyWeb-driven development
Description Logic (First Order)Foundation for formal reasoning
Easily create, share and reuse knowledge
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POPE Architecture
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Summary and Future Directions
Prediction is difficult, particularly about the future…..
Niels Bohr
Modeling Research in PSE: Opportunities
Beyond ODE, PDE, DAE ModelsOther kinds of Models
Signed Digraphs, Fault TreesPetri netsProduction rules, LogicAgents
Will play a crucial role as we automate more and more of the higher order reasoning now performed by humans
Opportunities for PSEInformatics
Models, Representations, OntologiesHigh Throughput Data MiningSustainable Energy Systems
Domain Specific CompilersCatalyst design, Pharmaceutical Engg
Semantic searchAutomated Entity Extraction and Recognition
Pharmaceutical EnggCS folks can help but can’t address these as they lack PSE domain knowledge
Not just programming
Intelligent Supervisory Control Framework
Intelligent MonitoringIntelligent Monitoring
Fault DiagnosisFault Diagnosis
Regulatory Control(MPC)
Regulatory Control(MPC)
ProcessProcess
Data AcquisitionData Acquisition
OperatorOperator
Data Reconciliation Parameter EstimationData Reconciliation Parameter Estimation
Supervisory ControlFault Administration
and RTOSupervisory ControlFault Administration
and RTO
Data
Data
Data Data
Manipulated Variables
Reconciled Data
Sens
or
Tren
ds
Faults
Faults FDDDesig n
Setpoint s
Cont
rolle
r Se
ttin
gs
Information Specifications
Parameter Estimates
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“Messy” road, not much traffic beforeProblems requiring Conceptual ClarityChallenging but fun I think we have made reasonable progress but…..Miles to go before we sleep…..
Adventures in Process Systems Engineering
The Road Less Traveled By
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Stopping by Woods on a Snowy EveningWhose woods these are I think I know.His house is in the village though;He will not see me stopping hereTo watch his woods fill up with snow.
My little horse must think it queerTo stop without a farmhouse nearBetween the woods and frozen lakeThe darkest evening of the year.
He gives his harness bells a shakeTo ask if there is some mistake.The only other sound's the sweepOf easy wind and downy flake.
The woods are lovely, dark and deep.But I have promises to keep,And miles to go before I sleep,And miles to go before I sleep.
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Thank You for Your Kind Attention!
Any Questions?