WebCAST on Friday, 03 Dec 2004, 10:00am-11:30am Pacific [1:00pm-2:30pm Eastern]

The 40 page presentation [5.6 MB] may be downloaded in pdf format. The complete paper is published in Computers and Chemical Engineering, Vol 29/1 pp 11-27, Special issue: PSE 2003 - Edited by B. Chen and A. W. Westerberg.

Abstract
In this web-cast presentation I will give an overview of decision making and portfolio management in highly distributed organizations. The business system is modeled as a flexible network of semi-autonomous activities integrated with the market through service, cash and product transactions. There is a positive cost associated which each activity and transaction (the second law of thermodynamics), whereas cash is conserved (the first law of thermodynamics). These foundation principles allow us to develop a very rich topological structure for finance and business decision making based on cost, cash-flow and value analysis.

The objective of the business decision maker is to manage the activity rates and project portfolio so that the “intrinsic value” of the enterprise is maximized without incurring undue risk. According to Warren Buffet, the intrinsic value is the expected, discounted cash value of a project. A project can be a process modification, R&D resulting in a new product or process or a merger or acquisition. In this presentation I will explain how the dynamics of the network of integrated activities and project portfolio can be managed using distributed decision making and how good inventory and flow control reduce cost and risk. Risk is modeled as a Martingale process driven by stochastic fluctuations in the market. I also show that under certain conditions the intrinsic value is maximized by decentralized decision making and that the policies we generate leads to methodologies for decision making which are similar to those recently advocated by “lean manufacture”.

By making analogies between network thermodynamics and business decision making I show that the network paradigm leads to organizational structures that are agile and able to adapt to changing markets and new technologies. Industrial examples from automotive windshield production, solar grade silicon and aluminum production will be discussed.

Biographical Sketch
Erik Ydstie is Professor of Chemical Engineering at Carnegie Mellon University. He received the B.Sc. and M.Sc. from the Norwegian Institute of Technology and his Ph.D. in 1982 from Imperial College. Professor Ydstie applies control theory to processes of practical interest to the chemical manufacturing industries.

Crystal Engineering for Product & Process Design

WebCAST on Thursday, 23 June 2005, 10:00am to noon Pacific [1:00pm-3:00pm Eastern]

The entire 47 page presentation [2.0 MB] may be downloaded in pdf format.

Abstract
Crystalline organic solids are ubiquitous as either final products or as intermediates in the specialty chemical, pharmaceutical, and home & personal care industries. Virtually all small molecular weight drugs are isolated as crystalline materials, and over 90% of all pharmaceutical products are formulated in particulate, generally crystalline form. Crystalline chemical intermediates, such as adipic acid, are produced in large amounts to make polymers and specialty products. Skin creams and other personal care product formulations contain crystalline solids. In most cases the properties of the crystalline solid have a major impact on the functionality of the product as well as the design and operation of the manufacturing process.

Crystal size (or size distribution), shape, enantiomorph, and polymorph all influence product functionality. For example, even a 50 micron particle in a hand cream makes the cream feel gritty. Size distribution is important in the manufacture of beta-carotene, which is virtually insoluble in water and only sparingly soluble in vegetable oils, and is used as a food colorant. The color shade given to the food is determined by the narrow size distribution which must be in the submicron range. Crystal shape and polymorph influence solubility, dissolution rate (which influence bioavailability), compressibility (important for tabletting), and stability. The crystal enantiomorph is of vital importance in the manufacture of chiral materials, which has become a $100 billion/year industry in recent years. The choice of solvent, as well as the design and operation of the manufacturing process determine the crystal properties. Moreover, crystal size distribution, and shape have a major impact on the design of the manufacturing process since needle-like crystals or plate-like crystals can be difficult to filter and dry.

In this presentation we discuss the interactions between crystal engineering and crystallization process & product design. We assess the current status of knowledge in this field and identify critical areas for future research and development.

Biographical Sketch
Michael F. Doherty is Professor of Chemical Engineering at the University of California, Santa Barbara. He received his B.Sc. in Chemical Engineering from Imperial College, University of London in 1973, and his Ph.D. in Chemical Engineering from Trinity College, University of Cambridge in 1977. He taught at the Universities of Minnesota and Massachusetts (where he reached the rank of University Distinguished Professor) before joining the faculty at UCSB. He has held a visiting appointment at the University of Minnesota in the Spring Quarter of 1981 and was a visiting scholar at the University of California at Berkeley for the 1984 calendar year. His research interests include design and synthesis of nonideal separation systems, separation with chemical reaction, and crystal engineering of organic materials. He is the holder of four patents, has published over 150 technical papers and delivered over 160 invited lectures; he was awarded best paper of the year in 1993 (jointly with M.F. Malone and Z.T. Fidkowski) and again in 2001 (jointly with M. F. Malone and S. B. Gadewar) by the editors of Computers and Chemical Engineering.

He is co-author of the textbook, Conceptual Design of Distillation Systems, McGraw-Hill (2001), and editor of the distillation chapters in Perry’s Handbook, and the Kirk-Othmer Encyclopedia of Chemical Technology. He has received numerous honors and awards for his teaching and research, including the Computing in Chemical Engineering Award of the CAST Division of the AIChE (awarded jointly with M. F. Malone in 1996), the Alpha Chi Sigma Award for Chemical Engineering Research of the AIChE (2004), the Clarence G. Gerhold Award of the Separations Division of the AIChE (2004) and the Excellence in Process Development Research Award of the Process Development Division of AIChE (awarded jointly with M. F. Malone in 2004). He has served as a consultant for many companies in the area of separations technology, and is a member of the Corporate Technical Advisory Boards for The Dow Chemical Company (2000-present) and Rhone–Poulenc (1997-1999).

At the University of Massachusetts Dr. Doherty was Head of Department from 1988-1997, and served as Director of the Center for Process Design and Control (1997-2000). He has been a Trustee of the CACHE Corporation since 1987 and served as its president from 2000-2002. In 1993 he was Chair of the Computing and Systems Technology Division of the AIChE. He serves as a member of the Editorial Boards for Computers and Chemical Engineering (1997-present), Process Systems Engineering Series, Academic Press (1997-present), Separation and Purification Methods (1998-2002), Industrial and Engineering Chemistry Research (1995-1998), and Transactions of the IChemE Part A: Chemical Engineering Research & Design (2001- 2003).

Advanced Process Control in Semiconductor Manufacturing

WebCAST on Friday, 28 October 2005, 10am-noon Pacific [1pm-3pm Eastern]

The entire 71 page presentation [3.3 MB] may be downloaded in pdf format.

Abstract
Semiconductor manufacturing error budgets are getting tighter and traditional metrology and control methods cannot keep up with the ever shrinking dimensions. In the sub-100nm generation of technologies, Critical Dimensions (CDs) are hard to measure, let alone control, since error budgets are almost consumed by measurement error. As a result, integrated circuit designers are called upon to produce designs that can tolerate large amounts of variability, and IC production facilities turn to more advanced process control schemes. This new reality challenges the historical modes of interaction between IC designers and producers. In this talk we will present this problem, and we will highlight present and future cutting edge applications in metrology, control, and design for manufacturability.

Biographical Sketches
COSTAS J. SPANOS received the EE Diploma from the National Technical University of Athens, Greece and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from Carnegie Mellon University. In 1988 he joined the faculty at the department of Electrical Engineering and Computer Sciences of the University of California at Berkeley, where he is now a Professor, and the Associate Dean for Research in the College of Engineering. Dr. Spanos was the editor of the IEEE Transactions on Semiconductor Manufacturing, and has published more than 130 referred publications.

His research interests include the development of flexible manufacturing systems, the application of statistical analysis in the design and fabrication of integrated circuits, and the development of novel sensors and computer-aided techniques. In 2000 he was elected Fellow of the IEEE for contributions and leadership in semiconductor manufacturing.

THOMAS SONDERMAN is the Director of Automated Precision Manufacturing (APM) Technology for AMD with global responsibility for the design, development and implementation of manufacturing technologies within AMD’s wafer fab and assembly operations.

Thomas has held numerous management and engineering positions during his 15-year tenure with AMD. Prior to joining AMD, Sonderman worked as a process control engineer for Monsanto Chemical Inc. He obtained a BS in Chemical Engineering from the University of Missouri in 1986 and a Masters degree in Electrical Engineering from National Technological University in 1991.

Thomas has a broad range of experience in the area of manufacturing automation and its application to high volume semiconductor fabrication. He is a highly sought-after speaker at industry conferences and is member of two advisory committees at the University of Texas: Chemical Engineering and Science, Technology and Society. Sonderman is the author of over 40 patents/patents pending and has published numerous articles in the area of automated control and manufacturing technology.

Feedback: The simple and best solution

WebCAST on Thursday, 9 Feb 2006, 9am-11am Pacific [noon-2pm Eastern]

The entire 66 page presentation [2863 KB] may be downloaded in pdf format.

Abstract
Most chemical engineers are (indirectly) trained to be “feedforward thinkers" and they immediately think of “model inversion'' when it comes doing control. Thus, they prefer to rely on models instead of data, although simple feedback solutions in many cases are much simpler and certainly more robust.

The seminar starts with a simple comparison of feedback and feedforward control and their sensitivity to uncertainty. Then two nice applications of feedback are considered:

1. Implementation of optimal operation by "self-optimizing control". The idea is to turn optimization into a setpoint control problem, and the trick is to find the right variable to control. Applications include process control, pizza baking, marathon running, biology and the central bank of a country.

2. Stabilization of desired operating regimes. Here feedback control can lead to completely new and simple solutions. One example would be stabilization of laminar flow at conditions where we normally have turbulent flow. I the seminar a nice application to anti-slug control in multiphase pipeline flow is discussed.

Biographical Sketch

Sigurd Skogestad was born in Norway in 1955. He received the Siv.Ing. degree (Diploma Engineer) in chemical engineering from the Norwegian University of Science and Technology (NTNU) in Trondheim in 1978. After finishing his military service at the Norwegian Defence Research Institute, he worked from 1980 to 1983 with Norsk Hydro in the areas of process design and simulation at their Reseach Center in Porsgrunn, Norway. He then spent 3.5 years in the US working towards his Ph.D. under the guidance of Manfred Morari, receiving the Ph.D. degree from the California Institute of Technology in 1987. He has been a professor of chemical engineering at the Norwegian University of Science and Technology (NTNU) since 1987, and since 1999 he is Head of Department of Chemical Engineering ( Kjemisk prosessteknologi ). He was at sabattical leave at the University of California at Berkeley in 1994-95, and at the University of California at Santa Barbara in 2001-02.

He has a group of about 10 Ph.D. students and is the Head of PROST which is the strong point center in process systems engineering in Trondheim and involves about 50 people in various departments.

The goal of his research is to develop simple yet rigorous methods to solve problems of engineering significance. Research interests include the use of feedback as a tool to (1) reduce uncertainty (including robust control), (2) change the system dynamics (including stabilization), and (3) generallly make the system more well-behaved (including self-optimizing control). Other interests include limitations on performance in linear systems, control structure design and plantwide control, interactions between process design and control, and distillation column design, control and dynamics.

The author of more than 100 journal publications and 150 conference publications, he is the principal author together with Ian Postlethwaite of the book "Multivariable feedback control" published by Wiley in 1996 (first edition) and 2005 (second edition). In October 2000 he published a book on "Process engineering - mass and energy balances" and a second edition came in August 2003 (In Norwegian; , Prosessteknikk (Tapir, 2000/2003) (he is considering writing an English edition.)

Dr. Skogestad was awarded "Innstilling to the King" for his Siv.Ing. degree in 1979, a Fullbright fellowship in 1983, received the Ted Peterson Award from AIChE in 1989, the George S. Axelby Outstanding Paper Award from IEEE in 1990, and the O. Hugo Schuck Best Paper Award from the American Automatic Control Council in 1992. He was an Editor of Automatica during the period 1996-2002.

In the autumn he teaches a course on introduction to process engineering based on his own text book. He used to teach the process control course for the 4th year students, but more recently this has been taken over by professor Heinz Preisig. Since 1989 he taught a Ph.D. course in robust multivariable control in the Control Department, based on his book with Ian Postlethwaite, but the course was given for the last time in spring 1999, and it has been replaced by an advanved undergraduate course given by Professor Morten Hovd. The engineering degree at NTNU has recently (first 5-year students graduated in 2002) changed from a 4.5 year program to a 5 year program and the siv.ing. degree is now considered equivalent to a M.Sc. degree. Professor Skogestad presentlty teaches a new advanced process control module for the 5th year students.

Computational Tools for the Analysis and Redesign of Microbial Production Systems

DATE: Friday, 12 May 2006, 10am-12noon Pacific [1pm-3pm Eastern]

The entire 46 page presentation [2105 KB] may be downloaded in pdf format.

Abstract
In this talk we will describe how optimization-based computational tools can be used to guide strain redesign leading to targeted overproductions. For example, production of bio-ethanol or complex molecules such as terpenes. Using as a starting point stoichiometric models of microbial metabolism, we will first explore how optimization can be used to pinpoint which new functionalities to add to the microbial host to endow it with new capabilities extracted from a generated database of more than 5,700 reactions. Building on this computational infrastructure, we will then present an integrated framework for identifying optimal microbial strain redesign strategies allowing for (i) additions, (ii) deletions and (iii) modulations (i.e., activations or inhibitions) of targeted reactions in the metabolic network. Finally we will explore how optimization can be used to analyze the topological properties of metabolic networks, identify pathway gaps and suggest ways of filling them. The developed computational tools will be highlighted using a number of design case-studies and the predictions will be contrasted with experimental results.

Biographical Sketch

Costas D. Maranas (b. 1967), Donald B. Broughton Professor, Department of Chemical Engineering, The Pennsylvania State University, BS, Chemical Engineering, Aristotle University, Greece, (1990); MA, Chemical Engineering, Princeton University (1992); Ph.D. in Chemical Engineering, Princeton University (1995); Allan P. Colburn Award for Excellence in Publication (2002), Editorial Board for Biophysical Journal, Computers & Chemical Engineering, Journal of Global Optimization and Metabolic Engineering; Reviewer for NSF, NIH and DOE; Research interests: Modeling and optimization of directed evolution protocols for protein engineering, analysis and optimization of metabolic and signaling networks, optimal design of biological circuits and synthetic biology, inference of gene regulatory networks, real options based optimization of product and R&D pipelines, optimization theory and algorithms.

Modeling and Design of Multiscale Chemical Systems

DATE: Friday, 29 Sept 2006, 10am-12noon Pacific [1pm-3pm Eastern]

The entire 41 page presentation [2.70 MB, pdf] may be downloaded from UIUC.

Abstract
This talk describes applications of molecular simulation to chemical reacting systems and the subsequent development of techniques for multiscale simulation and multiscale systems engineering. The progression of applications of simulation from macroscopic to molecular to multiscale is reviewed. Multiscale systems are presented as an approach that incorporates molecular and multiscale simulation to design processes that control events at the molecular scale while simultaneously optimizing all length scales from the molecular to the macroscopic. It is discussed how multiscale modeling and the targeted design of processes and products at the molecular scale can be addressed using the multiscale systems tools. In addition to addressing challenging problems in materials, microelectronics, and biotechnology, this provides a framework for addressing the “grand challenge” of nanotechnology: how to move nanoscale science and technology from art to an engineering discipline.

Biographical Sketch

Richard Braatz is Professor and Millennium Chair of Chemical and Biomolecular Engineering at the University of Illinois at Urbana-Champaign. Before starting at U of I he received M.S. & Ph.D. degrees from Caltech and spent a year at DuPont. Dr. Braatz is a co-author of ~100 journal papers and 3 books, and has consulted and/or collaborated with more than 10 companies including Merck, IBM, and UTC Fuel Cells. Honors and awards include the AACC Donald P. Eckman Award (2000), the ASEE Curtis W. McGraw Research Award (2004), the AIChE CAST Outstanding Young Researcher Award (2005), and the IEEE Antonio Ruberti Young Researcher Prize (2005). Dr. Braatz’s main research interests are in modeling, design, and control of complex and multiscale systems, with applications in microelectronics, pharmaceuticals, and biotechnology.

Model Predictive Control: Theory and Practice

DATE: Monday, 7 May 2007, 10am-12noon EST

The entire 64 page presentation [1772 KB] may be downloaded in pdf format.

Abstract
This course will attempt to give the audience a general overview on theories and practice of model predictive control and system identification. Fundamental theories as well as current industrial algorithms and practice will be covered. A short discussion on various system identification methods that are being used to build models for MPC will also be given.

Biographical Sketch
Dr. Lee is currently Director of the Integrated Sensing, System Identification, and Control Laboratory (ISSICL). His group is working on ways to use powerful computers, numerical optimization methods, information processing techniques, and novel sensors to improve the safety and efficiency of chemical and biological processes. The cornerstone of their research is a computer-based optimal control technique called Model Predictive Control (MPC), which has already seen applications on many industrial processes (>3000 worldwide applications) with some impressive results. The main components of MPC are the model, the sensors, and the optimal control algorithm. His research group focuses on integration - rather than mere enhancement of the individual components of MPC. They are developing modeling and system identification tools that allow the user to tailor the modeling efforts to specific end-goals of the control. They are developing techniques for integrating several different types of sensors and a process model so that accurate predictions can be made about the whole system including the behavior of those variables that cannot be measured as frequently or reliably as desired. They are also developing smart control algorithms that make optimal decisions while fully accounting for uncertainties in the model and sensed information. They are conducting a number of fundamental studies on data-assisted modeling, sensing, and control, which are designed to improve the integration step. In addition to the fundamental studies, they are conducting in parallel several application studies involving challenging industrial process control problems, including those that arise in particulate processes, mammalian cell reactors, polymer reactors, simulated moving bed separation systems, and pulp and paper processes.

Dr. Lee received the National Science Foundation’s Young Investigator Award and a number of other research and teaching awards. He is also a co-author of the forthcoming book “Model Predictive Control.” He is a member of AIChE, IEEE, and ASEE, and participated in organizing several international conferences.

Dynamic Real-Time Optimization: Concepts in Modeling, Algorithms and Properties

DATE: Wednesday, 28 November 2007, 10AM-noon EST

The entire 49 page presentation [5790 KB] may be downloaded in pdf format.

Abstract
The webcast develops and discusses nonlinear programming (NLP) strategies for the optimization of nonlinear dynamic models that arise in both off-line and on-line applications in chemical process engineering. In particular, Dynamic Real-Time Optimization can play a significant part in the decision-making hierarchy that includes logistics, planning, scheduling and control. Its basic components deal with estimation of the system and identification of a system model, optimization of a system model and regulation to reject disturbances. Moreover, the inclusion of a consistent set of nonlinear process models is essential in order to coordinate optimization decisions made at different levels in the hierarchy.

The webcast briefly presents and summarizes nonlinear programming methods for dynamic optimization. In particular, it discusses simultaneous NLP formulations along with large-scale NLP solvers for dynamic optimization and demonstrates its effectiveness with real-world examples. Also described is the extension of this approach to nonlinear model predictive control (NMPC). In the last few years, these have emerged as efficient and reliable on-line NMPC strategies.

Finally, the webcast discusses the integration of dynamic models for off-line optimization to on-line model predictive control (MPC). In particular, we will discuss a fast sensitivity-based nonlinear MPC strategy that is not only consistent with rigorous off-line dynamic optimization models but requires very little on-line computation. A similar strategy will also be presented for moving horizon estimation with nonlinear models. All of these concepts will be illustrated with several case studies drawn from process engineering.

Biographical Sketch
Professor Larry Biegler is the Bayer Professor of Chemical Engineering at Carnegie Mellon University. He received a BS degree from Illinois Institute of Technology and MS and PhD degrees from University of Wisconsin, Madison, all in chemical engineering. Prof. Biegler's research projects are in the areas of design research and systems analysis. His research centers on the development and application of concepts in optimization theory, operations research, and numerical methods for process design, analysis, and control. He has received numerous honors and awards including the Presidential Young Investigator Award from the National Science Foundation, the Curtis McGraw Research Award from the American Society for Engineering Education, and the Computing in Chemical Engineering Award from the CAST Division of the American Institute of Chemical Engineers.

When does controllability equal profitability?

DATE: Monday, 17 March 2008, 2 PM - 4 PM EST

The entire 68 page presentation [1674 KB] may be downloaded in pdf format.

Abstract
The justification of process control in the context of business decision-making may include the following economic or operating considerations: increased product throughput, increased yield of higher valued products, decreased energy consumption, decreased pollution, decreased off-specification product, improved safety, extended life of equipment, improved operability, and decreased production labor. However, identifying a direct relationship between each type of economic benefit (profitability) and how controllers are designed or operated (controllability) is an elusive target. Perspectives of how process control has influenced business decision-making have changed radically over the brief history of process control (1950 to the present). Thus it is valuable to have an historical view of the changing role of process control in operations and profit/loss measures. Today the influence of process control on business decision-making is at its highest level ever, but there are still many challenges that must be met for process control to maximize its economic impact on an enterprise-wide scale. The opportunity to connect controllability to profitability appears greater for batch processing than for continuous processing.

Biographical Sketch
Thomas F. Edgar is Professor of Chemical Engineering at the University of Texas at Austin and holds the George T. and Gladys Abell Chair in Engineering. Dr. Edgar received his B.S. in chemical engineering from the University of Kansas and a Ph.D. from Princeton University. For the past 35 years, he has concentrated his academic work in process modeling, control, and optimization, with over 200 articles and book chapters. Edgar has co-authored leading textbooks: Optimization of Chemical Processes (McGraw-Hill, 2001) and Process Dynamics and Control (Wiley, 2004). He has received major awards from AIChE (Colburn, Computing in Chemical Engineering, Lewis) and ASEE (Chemical Engineering Division, Westinghouse, and Meriam-Wiley). Recently he has carried out modeling and control research projects jointly with a variety of companies in the process industries under the auspices of the Texas-Wisconsin-California Control Consortium (www.che.utexas.edu/twmcc).

Multiscale Modeling and its Application to Catalyst Design and Portable Power Generation

DATE: Thursday, 24 April 2008, 2 PM - 4 PM EST

The entire 24 page presentation [1869 KB] may be downloaded in pdf format.

Abstract
Multiscale simulation is emerging as a new scientific field in chemical, materials, and biological sciences. The idea of multiscale modeling is straightforward: one computes information at a smaller (finer) scale and passes it to a model at a larger (coarser) scale by leaving out degrees of freedom as one moves from finer to coarser scales. The obvious goal of multiscale modeling is to predict macroscopic behavior of an engineering process from first principles (bottom-up approach). However, the emerging fields of nanotechnology and biotechnology impose new challenges and opportunities (top-down). For example, the miniaturization of microchemical systems for portable and distributed power generation imposes new challenges and opportunities than the conventional scaling up chemical engineers have worked on. In this talk, I will describe the development of multiscale models for catalytic reactors with a focus on small-scale hydrogen production. Limitations in model development, including multi-level uncertainty, will be discussed. A new multiscale and informatics-based framework will be presented for design of experiments (DOE) in order to enable model assessment and parameter refinement. The framework is designed to overcome uncertainties by allowing experimental data injection into multiscale models. Finally, I will discuss how one could use these models to enable both catalyst design and microsystem optimization for portable and distributed power generation.

Biographical Sketch
Dion Vlachos is a Professor at the Department of Chemical Engineering at the University of Delaware since 2003. He is currently an associate director of the Center for Catalytic Science and Technology. Dion obtained a five years diploma in Chemical Engineering from the National Technical Univ. of Athens, in Greece, in 1987. He obtained his MS and Ph.D. from the University of Minnesota in 1990 and 1992, respectively, and spent a postdoctoral year at the Army High Performance Computing Research Center, MN, after which he joined UMass as an Assistant Professor. He was promoted to an associate professor at UMass in 1998. Dion was a Visiting Fellow at Princeton University in the spring of 2000, a visiting faculty at Thomas Jefferson Univ. and Hospital in spring of 2007 and the George Pierce Distinguished Prof. of Chemical Engineering and Materials Science at the Univ. of Minnesota in the fall of 2007. Dion is the recipient of an ONR Young Investigator Award, a NSF Career Award, a Junior Faculty Award, and the Best Advisor Award (twice). He is a member of the American Institute of Chemical Engineers, American Chemical Society, The Combustion Institute, The Catalysis Society, and SIAM. His main research thrust is multiscale modeling and simulation along with their application to catalysis and portable microchemical devices for power generation, nucleation and growth of nanomaterials, microporous thin films, and molecular cell biology. He is the corresponding author of more than 160 refereed publications and has given more than 120 invited talks (plenary lectures, keynote lectures, etc.).