- Email: [email protected]
Introduction: 25 years of progress in process systems engineering
Computers and Chemical Engineering 28 (2004) 437–439
Introduction: 25 years of progress in process systems engineering R. W. H. Sargent∗ Department of Chemical Engineering and Chemical Technology, Imperial College of Science, University of London, Prince Consort Road, London SW7 2BY, UK Received 11 September 2002; accepted 8 September 2003
Developments in process systems engineering have been closely linked to developments in computing since the early days, when the advent of computers held out the promise that “if a problem could be precisely formulated, then in principle an algorithm could be developed to solve it and hence implemented and solved on a computer without the need for further human intervention or expertise”, thus making available the most advanced techniques to the practising engineer. Indeed, early computers provided no scope for human intervention once the computation was handed over to the computer, but by the late seventies computers were accessed via terminals, making computing a much more experimental, interactive process, and the viewpoint of process systems engineers had changed accordingly. The year 1977 was a bumper year for me, since three of my students obtained their Ph.D. in that year—David Mellefont on the use of optimal control to make best use of limited measurement capability in on-line control, Gerry Sullivan who applied optimal control to optimize the change-over between processing of different crude oils in the aftermath of the oil crisis, and Ignacio Grossmann, who involved me in the newer areas of heat exchanger network synthesis, the scheduling of multipurpose batch processes, design under uncertainty, and the world of integer programming. It was a time when “expert systems” arrived to generate entirely new ways of harnessing computers to tackle complex, ill-defined problems and to generate new controversies in the process engineering community. In 1979 there were two landmark conferences, one organized by David Rippin at Montreux, Switzerland, and the other by the American Chemical Society in Washington, which caught the mood and excitement of the time, and I think finally established the field of “process systems engineering”. ∗
Tel.: +44-207-589-5111; fax: +44-207-584-7596. E-mail address: [email protected] (R.W.H. Sargent).
0098-1354/$ – see front matter © 2003 Published by Elsevier Ltd. doi:10.1016/j.compchemeng.2003.09.032
1980 saw the start of a new series of conferences: “Foundations of Computer-Aided Process Design (FOCAPD)” under the auspices of the AIChE, the first of which was organized by Richard Mah and Warren Seider. There was a limited invited audience of a mix of academics and industrialists, with an emphasis on discussion of a series of state-of-the-art reviews. Much solid work on both general computational techniques and solutions of particular problems was presented over the week, but the excitement centred on the new approaches to process synthesis. I particularly remember Bodo Linnhoff’s flamboyant presentation (Linnhoff, 2003) of his “pinch technology” for energy saving. His talk was memorable for his story of the habit-conditioned hamster who went to every previous location in turn as his food was moved, and for his demonstrations in several examples that use of simple thermodynamic reasoning could reduce complex energy-saving problems to back-of-the-envelope calculations involving “just an afternoon’s work”. This repeated claim prompted the opening question from a sceptical industrialist: “Have you ever thought of working mornings as well?” This meeting was followed in 1982 by another major defining conference, organized by Professor Takamatsu in Kyoto, Japan, which launched the triennial international PSE series. Each morning was devoted to only two key-note talks, with the remaining time spent in free-ranging discussion. The speakers were drawn from a variety of countries, and covered the whole range of topics, including modelling, synthesis, design, operation, control, and underlying computer technology, as well as the nature and philosophy of process systems engineering itself. It is an education to re-read these key-note talks, and to realise that many issues and ideas now thought of as representing a “modern” viewpoint, were already appreciated, and possible solutions actively discussed at Kyoto. One of the immediate outcomes was to prompt George Stephanopoulos to develop his ideas for control into
438
R.W.H. Sargent / Computers and Chemical Engineering 28 (2004) 437–439
a new textbook for undergraduate teaching of control, which on its publication rapidly became the standard text world-wide, and fundamentally altered the traditional approaches. New ideas in “model predictive control”, building on Richalet’s (Richalet, Rault, Testud, & Papon, 1978) ideas, had already emerged, Dave Cutler (Cutler & Ramaker, 1979) at Shell in Houston was already successfully applying his “Dynamic Matrix Control (DMC)”, a combination of Richalet’s modelling ideas and a simple discrete-time, linear-quadratic on-line optimal controller, and Manfred Morari (Garcia & Morari, 1982) had produced his unifying concept of “internal model control” for the rational design of control systems, but the major impact of the DMC development on the whole industrial scene was yet to come from the formation of Cutler’s own company, the DMC Corporation. With triennial PSE conferences, FOCAPD meetings every 4 years, alternating with a similar series on Chemical Process Control and eventually sharing their slot with a series on “Foundations of Computer-Aided Operations”, and the European Federation of Chemical Engineering annual meetings on Computing Applications to Chemical Engineering, there was no shortage of outlets for the increasing avalanche of papers on process systems topics. During the eighties the focus remained on the chemical process itself, but with steadily increasing recognition of the environment within which the process must function. For example the outstanding event of FOCAPD 83 was the remarkable paper by Ignacio Grossmann and Manfred Morari: “A Dialog on Resiliency, Flexibility and Operability---Process Design Objectives for a Changing World” (Grossmann & Morari, 1983). In that year too, at the AIChE’s Diamond Jubilee Meeting, in my invited review of computer challenges (Sargent, 1983), I gave a decidedly up-beat review of the pace of developments and attempted an analysis of the far-reaching consequences for management, the universities, and even the profession. There was expansion too into a widening range of industries—the star attraction at PSE 85 in Cambridge, England, was an impressive poster by brothers George and Gregory Stephanopoulos on the synthesis of biochemical processes. The process control community started to widen their concerns to include process monitoring and fault detection. The H-infinity approach to control system design introduced a new paradigm for robust control in the face of uncertainty, and several groups started to consider the impact of the process design on the design of the control system. The rapid advances in computing capability meant that industrial users were tackling larger and larger problems, which had a major impact at the techniques level—and to add to our problems of grappling with large-scale dynamic simulation, we discovered and struggled to understand the hidden complexities of differential-algebraic systems.
Emilia Kondili, Costas Pantelides and I (Kondili, Pantelides, & Sargent, 1988) introduced the “state-task network” to describe multi-purpose batch processes, and our bold (foolhardy?) proposed algorithm to solve the short-term scheduling problem rigorously as a mixed-integer linear programming problem created new interest in optimal scheduling, while Sandro Macchietto (Sanchez & Macchietto, 1995) pursued the idea of systematically generating the complex operating procedures for multi-purpose plant at the implementation level, with automatic checking of completeness and integrity. Stimulated largely by the enthusiasm of George Stephanopoulos (Stephanopoulos, 1989), there was an increasing interest in Artificial Intelligence to expand the capabilities of expert systems, and discussion of this as an issue took centre stage at the third FOCAPD meeting in 1989, but most of this meeting was devoted to the different approaches to process synthesis which had emerged. Jim Douglas had earlier published several papers and his well known textbook: “Conceptual Design of Chemical Processes” (Douglas, 1988) and presented his now widely accepted hierarchical approach to design, emphasising economic incentive as the main tool for deciding priorities for more detailed investigation. Ignacio Grossmann described progress on his “outer-approximation” algorithm for mixed-integer programming and its application to optimizing “superstructures” (which embody many alternative configurations in a single flowsheet). Rex Reklaitis pointed out the vast additional complexities in design of batch processes and laid out a programme of research to deal with the issues. Chris Floudas considered the simultaneous synthesis of a process with its control system, and Mike Doherty described a rational scheme for using his “residue curve maps” to synthesise processes for separating azeotropic mixtures. The nineties saw the advent of artificial neural networks, with significant impact on fault detection techniques and on-line state estimation for control, and there were serious attempts to make use of nonlinear models and realistic economic objectives in on-line receding-horizon optimal control. There was a rise in popularity of “simulated annealing” and genetic algorithms for optimization, while the mathematicians produced the new theory of “wavelets”, providing a powerful technique for analysing multi-scale processes. There was also increasing interest in finding global rather than local solutions of optimization problems, and Chris Floudas (Adjiman, Androulakis, & Floudas, 1997) published his global optimization algorithm (GOP) already impressive at the time, but since greatly improved in its current version (ABB) (Adjiman, Androulakis, & Floudas, 1998)—and he has recently applied it even more impressively to predict molecular structures in protein folding (Floudas, 2001). Diane Hildebrandt and David Glasser (Hildebrant & Glasser, 1994) published their “convex hull” approach to solving the phase and chemical equilibrium problem, and used it to explore attainable products for separation and
R.W.H. Sargent / Computers and Chemical Engineering 28 (2004) 437–439
reaction systems, resolving some long-standing controversies. Mike Doherty (Doherty & Buzad, 1992) extended his approach to azeotropic distillation to cover reacting mixtures, furnishing a technique for the synthesis of reactive-distillation processes, and Ferenz Friedler (Friedler, Tarjan, Huang, & Fan, 1992) published his “accelerated branch-and-bound algorithm” with his “P-graph” representation of general process networks. GPROMS succeeded SPEEDUP, providing facilities for modelling operational sequences and equipment as well as processes, and adding capability to deal with partialdifferential-algebraic equations and “hybrid” systems, involving both discrete and continuous processes. Among all the aids now being showered on the hapless practising chemical engineer, we have at last started to give him more help at the basic modelling stage. Among other efforts, and motivated by the pioneering work of Hans Preisig (Preisig, Lee, Little, & Wright, 1989) on the modelling of life-support systems, we began work on the generation of mathematical models for dynamics from a purely physical description of the process, and reported encouraging success on lumped-parameter models at PSE 94 (Perkins, Sargent, & Vazquez-Roman, 1994). Kathy Hangos and Ian Cameron (Hangos & Cameron, 1997) proposed a formal language for specifying assumptions and generating the resulting models. However extension to distributed-parameter models leads us into the realm of computational fluid dynamics (CFD) and raises fundamental questions about the validity of assumptions we have long taken for granted. This is part of a more general rapprochement of these two fields which is long overdue and there has also been extension of interest into the realms of molecular chemistry and molecular dynamics (Stephanovic & Pantelides, 2000). The nineties too saw a further widening of the scope of process systems engineering from the concerns of integrated design and plant-wide control to the consideration of management issues for the whole enterprise, and even the whole supply chain. There seem to be no bounds to the increasing scope and depth of studies undertaken in the name of process systems engineering, and the pace seems to steadily increasing. This brief introduction cannot hope to do justice to the prolific developments of the past quarter-century, and is inevitably coloured by my own more limited range of interests and experiences, but I hope it is enough to whet the reader’s appetite for the more comprehensive reviews of the different areas which follow in this anniversary issue.
439
References Linnhoff, B. (2003). Entropy in practical process design (pp. 537–572), FOCAPD 1. Richalet, J. A., Rault, A., Testud, J. L., & Papon, J. (1978). Model predictive heuristic control: Applications to an industrial process. Automatica, 14, 413–428. Cutler, C. R., & Ramaker, B. L. (1979). Dynamic matrix control—A computer control algorithm. Paper WP5-B, AIChE National Meeting, Houston, USA. Garcia, C. E., & Morari, M. (1982). Internal model control-1. A unifying review and some new results. Industrial and Engineering Chemistry and Process Design Development, 21, 308–323. Grossmann, I. E., & Morari, M. A. (1983). Dialog on resiliency, flexibility and operability—Process design objectives for a changing world, FOCAPD’1983. Sargent, R. W. H. (1983). Computers in chemical engineering—Challenges and constraints. AIChE Symposium Series, 79(235), 57–64. Kondili, E., Pantelides, C.C., & Sargent, R.W.H. (1988). A general algorithm for scheduling batch operations, PSE’88. Sanchez, A., & Macchietto, S. (1995). Design of procedural controllers for chemical processes. Computers and Chemical Engineering, 19, S381–S386. Stephanopoulos, G. (1989). Artificial intelligence and symbolic computing in process engineering design (pp. 21–48), FOCAPD’1989. Douglas, J. M. (1988). Conceptual design of chemical processes. New York: McGraw Hill. Adjiman, C. S., Androulakis, I. P., & Floudas, C. A. (1997). Global optimization of MINLP problems in process synthesis and design. Computers and Chemical Engineering, 21, S445–S450. Adjiman, C. S., Androulakis, I. P., & Floudas, C. A. (1998). A global optimization method ABB for twice differentiable NLPs—II Implementation and computational results. Computers and Chemical Engineering, 22(9), 1159–1179. Floudas, C. A. (2001). Structure prediction in protein folding, presented at the meeting at Imperial College, London in November 2001 to celebrate Roger Sargent’s 75th birthday. Hildebrant, D., & Glasser, D. (1994). Predicting phase and chemical equilibrium using the convex hull of the Gibbs free energy. Chemical Engineering Journal, 54, 187–197. Doherty, M. F., & Buzad, G. (1992). Reactive distillation by design. Transaction I. ChemE, 70, 448–454. Friedler, F., Tarjan, K., Huang, Y. W., & Fan, L. T. (1992). Graph-theoretic approach to process synthesis: Axioms and theorems. Chemical Engineering Science, 47, 1973–1988. Preisig, H. A., Lee, T. Y., Little, F., & Wright, B. (1989). On the representation of life-support system models, 19th Inter-Society Conference on Environmental Systems, San Diego, USA, July. Perkins, J. D., Sargent, R. W. H., & Vazquez-Roman, R. (1994). Computer generation of process models (vol. 1, pp. 123–125), PSE’94. Hangos, K. M., & Cameron, I. T. (1997). The formal representation of process system modelling assumptions and their implications. Computers and Chemical Engineering, 21, S823–S828. Stephanovic, J., & Pantelides, C. C. (2000). Towards tighter integration of molecular dynamics within process and product design computations (pp. 236–249), FOCAPD’2000.
Introduction: 25 years of progress in process systems engineering R. W. H. Sargent∗ Department of Chemical Engineering and Chemical Technology, Imperial College of Science, University of London, Prince Consort Road, London SW7 2BY, UK Received 11 September 2002; accepted 8 September 2003
Developments in process systems engineering have been closely linked to developments in computing since the early days, when the advent of computers held out the promise that “if a problem could be precisely formulated, then in principle an algorithm could be developed to solve it and hence implemented and solved on a computer without the need for further human intervention or expertise”, thus making available the most advanced techniques to the practising engineer. Indeed, early computers provided no scope for human intervention once the computation was handed over to the computer, but by the late seventies computers were accessed via terminals, making computing a much more experimental, interactive process, and the viewpoint of process systems engineers had changed accordingly. The year 1977 was a bumper year for me, since three of my students obtained their Ph.D. in that year—David Mellefont on the use of optimal control to make best use of limited measurement capability in on-line control, Gerry Sullivan who applied optimal control to optimize the change-over between processing of different crude oils in the aftermath of the oil crisis, and Ignacio Grossmann, who involved me in the newer areas of heat exchanger network synthesis, the scheduling of multipurpose batch processes, design under uncertainty, and the world of integer programming. It was a time when “expert systems” arrived to generate entirely new ways of harnessing computers to tackle complex, ill-defined problems and to generate new controversies in the process engineering community. In 1979 there were two landmark conferences, one organized by David Rippin at Montreux, Switzerland, and the other by the American Chemical Society in Washington, which caught the mood and excitement of the time, and I think finally established the field of “process systems engineering”. ∗
Tel.: +44-207-589-5111; fax: +44-207-584-7596. E-mail address: [email protected] (R.W.H. Sargent).
0098-1354/$ – see front matter © 2003 Published by Elsevier Ltd. doi:10.1016/j.compchemeng.2003.09.032
1980 saw the start of a new series of conferences: “Foundations of Computer-Aided Process Design (FOCAPD)” under the auspices of the AIChE, the first of which was organized by Richard Mah and Warren Seider. There was a limited invited audience of a mix of academics and industrialists, with an emphasis on discussion of a series of state-of-the-art reviews. Much solid work on both general computational techniques and solutions of particular problems was presented over the week, but the excitement centred on the new approaches to process synthesis. I particularly remember Bodo Linnhoff’s flamboyant presentation (Linnhoff, 2003) of his “pinch technology” for energy saving. His talk was memorable for his story of the habit-conditioned hamster who went to every previous location in turn as his food was moved, and for his demonstrations in several examples that use of simple thermodynamic reasoning could reduce complex energy-saving problems to back-of-the-envelope calculations involving “just an afternoon’s work”. This repeated claim prompted the opening question from a sceptical industrialist: “Have you ever thought of working mornings as well?” This meeting was followed in 1982 by another major defining conference, organized by Professor Takamatsu in Kyoto, Japan, which launched the triennial international PSE series. Each morning was devoted to only two key-note talks, with the remaining time spent in free-ranging discussion. The speakers were drawn from a variety of countries, and covered the whole range of topics, including modelling, synthesis, design, operation, control, and underlying computer technology, as well as the nature and philosophy of process systems engineering itself. It is an education to re-read these key-note talks, and to realise that many issues and ideas now thought of as representing a “modern” viewpoint, were already appreciated, and possible solutions actively discussed at Kyoto. One of the immediate outcomes was to prompt George Stephanopoulos to develop his ideas for control into
438
R.W.H. Sargent / Computers and Chemical Engineering 28 (2004) 437–439
a new textbook for undergraduate teaching of control, which on its publication rapidly became the standard text world-wide, and fundamentally altered the traditional approaches. New ideas in “model predictive control”, building on Richalet’s (Richalet, Rault, Testud, & Papon, 1978) ideas, had already emerged, Dave Cutler (Cutler & Ramaker, 1979) at Shell in Houston was already successfully applying his “Dynamic Matrix Control (DMC)”, a combination of Richalet’s modelling ideas and a simple discrete-time, linear-quadratic on-line optimal controller, and Manfred Morari (Garcia & Morari, 1982) had produced his unifying concept of “internal model control” for the rational design of control systems, but the major impact of the DMC development on the whole industrial scene was yet to come from the formation of Cutler’s own company, the DMC Corporation. With triennial PSE conferences, FOCAPD meetings every 4 years, alternating with a similar series on Chemical Process Control and eventually sharing their slot with a series on “Foundations of Computer-Aided Operations”, and the European Federation of Chemical Engineering annual meetings on Computing Applications to Chemical Engineering, there was no shortage of outlets for the increasing avalanche of papers on process systems topics. During the eighties the focus remained on the chemical process itself, but with steadily increasing recognition of the environment within which the process must function. For example the outstanding event of FOCAPD 83 was the remarkable paper by Ignacio Grossmann and Manfred Morari: “A Dialog on Resiliency, Flexibility and Operability---Process Design Objectives for a Changing World” (Grossmann & Morari, 1983). In that year too, at the AIChE’s Diamond Jubilee Meeting, in my invited review of computer challenges (Sargent, 1983), I gave a decidedly up-beat review of the pace of developments and attempted an analysis of the far-reaching consequences for management, the universities, and even the profession. There was expansion too into a widening range of industries—the star attraction at PSE 85 in Cambridge, England, was an impressive poster by brothers George and Gregory Stephanopoulos on the synthesis of biochemical processes. The process control community started to widen their concerns to include process monitoring and fault detection. The H-infinity approach to control system design introduced a new paradigm for robust control in the face of uncertainty, and several groups started to consider the impact of the process design on the design of the control system. The rapid advances in computing capability meant that industrial users were tackling larger and larger problems, which had a major impact at the techniques level—and to add to our problems of grappling with large-scale dynamic simulation, we discovered and struggled to understand the hidden complexities of differential-algebraic systems.
Emilia Kondili, Costas Pantelides and I (Kondili, Pantelides, & Sargent, 1988) introduced the “state-task network” to describe multi-purpose batch processes, and our bold (foolhardy?) proposed algorithm to solve the short-term scheduling problem rigorously as a mixed-integer linear programming problem created new interest in optimal scheduling, while Sandro Macchietto (Sanchez & Macchietto, 1995) pursued the idea of systematically generating the complex operating procedures for multi-purpose plant at the implementation level, with automatic checking of completeness and integrity. Stimulated largely by the enthusiasm of George Stephanopoulos (Stephanopoulos, 1989), there was an increasing interest in Artificial Intelligence to expand the capabilities of expert systems, and discussion of this as an issue took centre stage at the third FOCAPD meeting in 1989, but most of this meeting was devoted to the different approaches to process synthesis which had emerged. Jim Douglas had earlier published several papers and his well known textbook: “Conceptual Design of Chemical Processes” (Douglas, 1988) and presented his now widely accepted hierarchical approach to design, emphasising economic incentive as the main tool for deciding priorities for more detailed investigation. Ignacio Grossmann described progress on his “outer-approximation” algorithm for mixed-integer programming and its application to optimizing “superstructures” (which embody many alternative configurations in a single flowsheet). Rex Reklaitis pointed out the vast additional complexities in design of batch processes and laid out a programme of research to deal with the issues. Chris Floudas considered the simultaneous synthesis of a process with its control system, and Mike Doherty described a rational scheme for using his “residue curve maps” to synthesise processes for separating azeotropic mixtures. The nineties saw the advent of artificial neural networks, with significant impact on fault detection techniques and on-line state estimation for control, and there were serious attempts to make use of nonlinear models and realistic economic objectives in on-line receding-horizon optimal control. There was a rise in popularity of “simulated annealing” and genetic algorithms for optimization, while the mathematicians produced the new theory of “wavelets”, providing a powerful technique for analysing multi-scale processes. There was also increasing interest in finding global rather than local solutions of optimization problems, and Chris Floudas (Adjiman, Androulakis, & Floudas, 1997) published his global optimization algorithm (GOP) already impressive at the time, but since greatly improved in its current version (ABB) (Adjiman, Androulakis, & Floudas, 1998)—and he has recently applied it even more impressively to predict molecular structures in protein folding (Floudas, 2001). Diane Hildebrandt and David Glasser (Hildebrant & Glasser, 1994) published their “convex hull” approach to solving the phase and chemical equilibrium problem, and used it to explore attainable products for separation and
R.W.H. Sargent / Computers and Chemical Engineering 28 (2004) 437–439
reaction systems, resolving some long-standing controversies. Mike Doherty (Doherty & Buzad, 1992) extended his approach to azeotropic distillation to cover reacting mixtures, furnishing a technique for the synthesis of reactive-distillation processes, and Ferenz Friedler (Friedler, Tarjan, Huang, & Fan, 1992) published his “accelerated branch-and-bound algorithm” with his “P-graph” representation of general process networks. GPROMS succeeded SPEEDUP, providing facilities for modelling operational sequences and equipment as well as processes, and adding capability to deal with partialdifferential-algebraic equations and “hybrid” systems, involving both discrete and continuous processes. Among all the aids now being showered on the hapless practising chemical engineer, we have at last started to give him more help at the basic modelling stage. Among other efforts, and motivated by the pioneering work of Hans Preisig (Preisig, Lee, Little, & Wright, 1989) on the modelling of life-support systems, we began work on the generation of mathematical models for dynamics from a purely physical description of the process, and reported encouraging success on lumped-parameter models at PSE 94 (Perkins, Sargent, & Vazquez-Roman, 1994). Kathy Hangos and Ian Cameron (Hangos & Cameron, 1997) proposed a formal language for specifying assumptions and generating the resulting models. However extension to distributed-parameter models leads us into the realm of computational fluid dynamics (CFD) and raises fundamental questions about the validity of assumptions we have long taken for granted. This is part of a more general rapprochement of these two fields which is long overdue and there has also been extension of interest into the realms of molecular chemistry and molecular dynamics (Stephanovic & Pantelides, 2000). The nineties too saw a further widening of the scope of process systems engineering from the concerns of integrated design and plant-wide control to the consideration of management issues for the whole enterprise, and even the whole supply chain. There seem to be no bounds to the increasing scope and depth of studies undertaken in the name of process systems engineering, and the pace seems to steadily increasing. This brief introduction cannot hope to do justice to the prolific developments of the past quarter-century, and is inevitably coloured by my own more limited range of interests and experiences, but I hope it is enough to whet the reader’s appetite for the more comprehensive reviews of the different areas which follow in this anniversary issue.
439
References Linnhoff, B. (2003). Entropy in practical process design (pp. 537–572), FOCAPD 1. Richalet, J. A., Rault, A., Testud, J. L., & Papon, J. (1978). Model predictive heuristic control: Applications to an industrial process. Automatica, 14, 413–428. Cutler, C. R., & Ramaker, B. L. (1979). Dynamic matrix control—A computer control algorithm. Paper WP5-B, AIChE National Meeting, Houston, USA. Garcia, C. E., & Morari, M. (1982). Internal model control-1. A unifying review and some new results. Industrial and Engineering Chemistry and Process Design Development, 21, 308–323. Grossmann, I. E., & Morari, M. A. (1983). Dialog on resiliency, flexibility and operability—Process design objectives for a changing world, FOCAPD’1983. Sargent, R. W. H. (1983). Computers in chemical engineering—Challenges and constraints. AIChE Symposium Series, 79(235), 57–64. Kondili, E., Pantelides, C.C., & Sargent, R.W.H. (1988). A general algorithm for scheduling batch operations, PSE’88. Sanchez, A., & Macchietto, S. (1995). Design of procedural controllers for chemical processes. Computers and Chemical Engineering, 19, S381–S386. Stephanopoulos, G. (1989). Artificial intelligence and symbolic computing in process engineering design (pp. 21–48), FOCAPD’1989. Douglas, J. M. (1988). Conceptual design of chemical processes. New York: McGraw Hill. Adjiman, C. S., Androulakis, I. P., & Floudas, C. A. (1997). Global optimization of MINLP problems in process synthesis and design. Computers and Chemical Engineering, 21, S445–S450. Adjiman, C. S., Androulakis, I. P., & Floudas, C. A. (1998). A global optimization method ABB for twice differentiable NLPs—II Implementation and computational results. Computers and Chemical Engineering, 22(9), 1159–1179. Floudas, C. A. (2001). Structure prediction in protein folding, presented at the meeting at Imperial College, London in November 2001 to celebrate Roger Sargent’s 75th birthday. Hildebrant, D., & Glasser, D. (1994). Predicting phase and chemical equilibrium using the convex hull of the Gibbs free energy. Chemical Engineering Journal, 54, 187–197. Doherty, M. F., & Buzad, G. (1992). Reactive distillation by design. Transaction I. ChemE, 70, 448–454. Friedler, F., Tarjan, K., Huang, Y. W., & Fan, L. T. (1992). Graph-theoretic approach to process synthesis: Axioms and theorems. Chemical Engineering Science, 47, 1973–1988. Preisig, H. A., Lee, T. Y., Little, F., & Wright, B. (1989). On the representation of life-support system models, 19th Inter-Society Conference on Environmental Systems, San Diego, USA, July. Perkins, J. D., Sargent, R. W. H., & Vazquez-Roman, R. (1994). Computer generation of process models (vol. 1, pp. 123–125), PSE’94. Hangos, K. M., & Cameron, I. T. (1997). The formal representation of process system modelling assumptions and their implications. Computers and Chemical Engineering, 21, S823–S828. Stephanovic, J., & Pantelides, C. C. (2000). Towards tighter integration of molecular dynamics within process and product design computations (pp. 236–249), FOCAPD’2000.