Process synthesis prospective

Computers and Chemical Engineering 28 (2004) 441–446

Process synthesis prospective Scott D. Barnicki, Jeffrey J. Siirola∗ Eastman Research Division, Eastman Chemical Company, P.O. Box 1972, Kingsport, TN 37662-5150, USA Received 15 July 2002; accepted 8 September 2003

Abstract Chemical process synthesis methods and tools developed over the last several decades have reached a level of maturity that have provided advantage to practitioners in an environment of increased costs and shrinking margins. Future growth within the chemical process industries is likely to involve even keener competition with greater impact from factors such as raw material and energy availability, climate change mitigation, sustainability, and inherent security. The future will probably see an expanded role for the systematic generation process synthesis paradigm, including an increased interdependency with process and catalytic chemistry on one hand and operability and control expertise on the other. Advances from artificial intelligence may inspire new process synthesis paradigms incorporating more effective representations of the underlying physical sciences and engineering art, new social concerns, new design strategies, and new computerized implementations. The future may also see a collaboration of the systematic generation and superstructure optimization process synthesis paradigms in which systematic generation is used to create the superstructure for simultaneous discrete and continuous variable optimization. As the resulting process designs will certainly be evaluated from additional points of view including social considerations, superstructure optimization will need to produce families of good designs for multi-criteria Pareto optimization. There are many challenges, but continued progress will be made and these challenges will be met. © 2003 Elsevier Ltd. All rights reserved. Keywords: Process synthesis; Systematic generation; Artificial intelligence; Representations; Superstructure optimization; Sustainability; Multi-criteria optimization

1. Introduction While every chemical process that ever existed was necessarily created, the development of systematic methods and tools for process invention or synthesis are relatively recent. Professor Westerberg’s retrospective article in this issue traces the historical development of methods for the generation of heat exchanger networks, separation trains, reactor systems, and complete flow sheets, and in particular the role of paradigm, representation, heuristics, search, and mathematical programming in this enterprise. Many process synthesis methods have reached a sufficient state of maturity to be used seriously within operating companies, by engineering and consulting firms, as well as in academic process design education. For example, we have found task-oriented hierarchical systematic generation approaches based on goal and constraint-directed means-ends analysis paradigms (with a particular emphasis on task coor∗

Corresponding author. E-mail address: [email protected] (J.J. Siirola).

0098-1354/$ – see front matter © 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.compchemeng.2003.09.030

dination, integration, and problem representation) to be especially effective (Barnicki & Siirola, 1997, 2001; Siirola, 1995, 1996a,b). Despite nearly four decades of interesting research progress on systematic process synthesis and process integration methods and tools, and a myriad of claims for the virtues and benefits therein, the penetration of these methods is somewhat less than might have been expected. In this article we will discuss the current climate facing the processing industries, how that climate may impact the process design enterprise, and speculate on future process synthesis capabilities.

2. Brief history and present state of the processing industries It is said that we have entered the post-industrial information age. A supposed characteristic of this new age is the increased importance of content (data, interpretation, knowledge) contrasted with artifacts (e.g., structures,

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S.D. Barnicki, J.J. Siirola / Computers and Chemical Engineering 28 (2004) 441–446

houses, vehicles, consumer goods). While the increasing importance of information cannot be denied, the diminution of importance of artifacts and of the materials that enable them may have been somewhat overstated. The processing industries are concerned with the manufacture of materials, the building blocks of artifacts. They have their roots in ancient agriculture and metallurgy and progressed in early times to brick and cement, dyes and pigments, soap and spirits. Early processes often involved only isolation and purification of useful natural substances, but evolved to increasingly more complex physical and chemical transformations, including inorganic, organic and biochemical reactions. More than a century ago advances in the science of synthetic organic chemistry led to the creation of molecular structures permitted by the laws of chemistry but not necessarily existing naturally on Earth. There followed the first large expansion in the chemical processing industry to make synthetic dyes from byproducts of coke production for steel manufacture. Also at that time, synthetic routes were being developed to molecular structures that did exist in nature, but were uneconomical to isolate from natural sources (e.g., aspirin). Soon processes were invented for a large number of organic substances that found uses as solvents, coatings, medicines, and intermediates in other chemical syntheses. Coal, wood, and other animal and agricultural products were the principal raw materials for the industry. German companies came to dominate the high technology arena of the era, competition was stifled by “gentleman’s agreements”, and chemical engineering was still more of an art than a science. More than 75 years ago attention in the chemical industry shifted to polymers. Early synthetic polymers were processed from or derivitized from natural polymers (e.g., rayon and cellulose acetate), or were designed to mimic natural macromolecules, like phenol-formaldehyde resin (Bakelite). Later, different chemistries were invented to grow polymers repeatedly from small units, giving rise to polyamides (nylons), polyesters, polycarbonates, polyurethanes, polystyrenes and polyolefins. Explosive growth of polymer applications fueled concomitant expansion in monomers, solvents, and intermediates production. Ethylene, propylene, carbon monoxide, hydrogen, simple aromatics, and other petroleum- and natural gas-derived hydrocarbons became (and still are) the fundamental raw materials for the industry. In addition, tremendous advances occurred in the pharmaceutical industry, agricultural applications, food processing industries, and in the adaptation of processing-like technologies to the actual fabrication of artifacts, e.g., photographic film and microelectronic devices. All of these contributed to spectacular growth within the chemical processing industries. This second large growth surge was characterized by the construction of many processes for the production of polymers and their intermediates. It was during this period that the science of chemical engineering unit operations reached

a relatively mature state. Sufficient experience accumulated to enable the formation of design heuristics and design by analogy. Computational power increased sufficiently and systematic methods and tools for process synthesis began to be developed. Perhaps 25 years ago, or so, the rate of growth driven by polymer substitution began to slow. Applications for materials substitution began to be saturated. With slower growth rates came keener competition and squeezed margins. New plant construction also began to slow, and with lower anticipated margins, some companies searched for more economical design solutions, some of which were enabled by the new process synthesis tools. Also about this time two politically driven worldwide oil supply disruptions resulted in an order of magnitude increase in energy and petroleum-derived raw material costs. Again, process synthesis tools, especially process integration tools, were brought to bear, as for a period of time the ratio of the costs of energy and capital varied somewhat from the traditional relationship. Despite a generally good acceptance by the public for the products of the processing industries (and the artifacts made from them), the industry itself was held in generally low esteem. Poor past environmental performance lead to increased governmental regulation and restrictions. Overall, this difficult period has left its legacy: no greenfield chemical sites have been constructed in the United States since that time. In academic circles, there was serious discussion about whether continuous process design was still an appropriate part of a modern chemical engineering curriculum, or whether the emphasis should shift to retrofit design, or the design of batch plants for specialty and pharmaceutical chemicals. Meanwhile, faced with saturation of markets the chemical processing industries began to look at a different avenue for growth: globalization. The developed world, with perhaps fifteen percent of the total population, produces over half of the total gross national product. The shear size of the rest of the world and the prospects for its increased standard of living engendered a vision of potential markets too big for many chemical processing companies to ignore. Plant expansions began to be predicated on an export business model. Politicians assisted by negotiating lower trade barriers. And in cases where oceanic shipment seemed uncompetitive, companies became multinational and designed plants for construction overseas. Globalization has certainly become a challenge for the processing industries. Taking advantage of lower trade barriers and to raise hard currency, entrepreneurs and state-supported industries in the developing world have built numerous chemical processes for export back to the developed world. Furthermore, in cases where markets have not grown in the developing world quite as fast as anticipated, material from plants recently built there by outside companies sometimes also is diverted back to the developed world. In general, these new plants use the latest technology and produce excellent materials equal in quality to that made anywhere. The result is that while overall world


markets are indeed growing, competition is now worldwide and unrelenting. For the foreseeable future, there will be many more players within the chemical processing industries, but the markets will likely continue to grow. The average standard of living in the developing world may quintuple or more within the next 50 years. The advantage will go to the competitor with a superior cost structure. The ability to invent and quickly implement advantaged technology will continue to grow in importance. There will, however, be even new challenges. An emphasis on environmental impact minimization will become as important in all parts of the world as it has been in the developed world for the last several decades. In addition, new factors will impact process chemistry and design choices including legitimate concerns for sustainability (not limiting the quality of life or options available to future generations), climate change, intrinsic safety, and now also intrinsic security. Nevertheless, these same challenges certainly will result in more opportunities for the processing industries. Different sources of basic raw materials are likely. Different systems for energy production, storage, transmission, and use are likely. Greenhouse gas management is likely. Nuclear, solar, and hydrogen may play increasingly important roles. The pace of development of novel artifacts, technologies for their manufacture, and material performance needs undoubtedly will quicken rather than decelerate.

3. Process synthesis prospective How might process synthesis methods and tools evolve in response to the challenges the chemical processing industry is likely to face? We offer the following speculations. 3.1. Reconsideration of many traditional raw materials, processes, and assumptions The challenges facing competitors in the chemical processing industries will demand the invention of more, not fewer, manufacturing processes. These processes may likely start from different raw materials than commonly employed today. This is because oil and natural gas, the common starting blocks today may become more expensive, may be less generally available, or not locally available at all. Other raw materials, both old such as coal, and new such as plants cultivated specifically as process feedstocks, may be employed. Also different intermediates, whose specific economics in the future could be very different from what they are today, may become important starting points for some processes. Along with these different raw materials will of course come different chemical routes to the desired products. Many of these routes are known today, and many more will be invented. Catalysts or perhaps biocatalysts will facilitate al-

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most all. Each of these will be invented or tailored especially for each purpose. However, the fundamental goal of process synthesis will remain the invention of detailed processes to exploit these chemistries at the desired scale, safely, environmentally responsibly, efficiently, and economically in a manner superior to all other possible processes. It is very likely that the relative importance of many design factors will be radically altered in the future. The source and cost of energy, the avoidance of climatic impact, materials of construction, and the portfolio of available unit operations may be very different from today. As a result, many of the common design heuristics based on tradeoffs among factors in today’s context may not be applicable in the future. It will be necessary to continually reevaluate heuristics and other design assumptions in light of changing practices, constraints, and economics before they are used. 3.2. Systematic generation of alternatives Although process synthesis methods based on experience, evolution, and pure mathematical formulations are all in use, we believe systematic generation methods will continue to be the most effective and broadly applicable in the future. These methods build up one or more designs given the goals and constraints of the processing problem. Past systematic generation methods have been based on paradigms derived from (1) expert design practice, as in PIP (Kirkwood, Locke, & Douglas, 1988); (2) artificial intelligence planning paradigms, as in the means-ends analysis of AIDES (Siirola & Rudd, 1971); and (3) resolution theorem-proving, as in BALTAZAR (Mahalec & Motard, 1977). Different design generation paradigms could very well be developed in the future. The artificial intelligence community might again be a source of inspiration. Much progress continues to be made in such areas as game players, theorem provers, and planners for robots and other autonomous devices. It should be remembered that many chemical processes (but not all, e.g., pharmaceutical processes) make wide use of the fundamental concept of recycle of both materials and energy for a number of purposes including efficiency and simplification. However, recycle is not generally included within the repertoire of game players, theorem provers, robot planners, and the like. This could become an important research area. Chemical process design is a very complex task. All previous systematic generation approaches have decomposed the design into a hierarchical series of subproblems such as reaction subsystems, basic material input–output-recycle structure, separation and purification subsystems, energy and power subsystems, environmental protection subsystems, and the like. As presently formulated these subproblems are not entirely independent, but rather interact in often complex ways. The formulation, coordination, integration, and overall control of subproblem solutions have a major impact on the performance of the current generation of process synthesis methods and especially on the optimality

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of the process designs generated. They can be expected to be major factors in the future as well. The chemical process engineering art is likely to change. Occasionally, new unit operations are invented and new phenomena are exploited to perform desired tasks. Distillation and other largely equilibrium-based separation methods such as extraction and crystallization have reached high levels of technical and application maturity. They have been and probably will continue to be mainstays of the industry in the foreseeable future. However, many still relatively immature rate-based separation methods, such as membrane permeation, large-scale chromatography, ion exchange, electrophoresis among others may find much broader application. All of these methods will continue to garner benefits from continued materials evolution and sometimes revolutions of the future. Relationships and trade-offs that set the size of equipment today may no longer be valid in light of new constraints or economic relationships. As many have suggested, future equipment may be designed with greater driving forces, smaller dimensions, more area per given volume, or otherwise intensified. This intensification will most certainly involve new unit operations combining reactions and separations. One example, reactive distillation has begun to find wider application, while more novel concepts such as membrane reactors are just beginning to be exploited. Systematic generation procedures and design heuristics will need to be updated as new technologies, unit operations, standards, constraints, or art are developed. The power of many current process synthesis methods lies in the implicit relationship between the underlying chemical and physical science of unit operations and the knowledge of which combinations lead to advantaged designs. This knowledge is often encoded in a representation appropriate for human abilities, and sometimes encoded in a manner particularly convenient for automated computer manipulation. Much of the most influential research in the process synthesis field in the last decade has been in the development of new representations of parts of the underlying science, or of the feasible exploitation of that science by potential equipment to accomplish desirable goals. A prime example of this phenomenon has been the development and widespread application of practical methods of generating and understanding residue curve maps for azeotropic systems (Barnicki & Siirola, 1997; Doherty & Malone, 2001). It is anticipated that much future research will also be devoted to understanding and representing how various phenomena may be beneficially exploited, in particular rate-based phenomena that cannot be expressed as readily as equilibrium-based phenomena. The results of such research will materially alter the course of process synthesis methods and tools development. While some process synthesis methods have been automated, many others have not. In some cases this is because representations that are suitable for human use have not yet been converted into a form suitable for computer implementation. Humans excel at interpreting graphical representations. Computers still largely fail at similar tasks.

Witness the evolution of distillation design methods. They began with graphical, dimensionally limited methods such as McCabe–Thiele diagrams. They have advanced to fully machine-coded numerical equilibrium and rate-based models in which essentially an infinite number of components can be handled. A similar evolution is occurring with residue curve maps. Three and four component systems can be represented in 3D graphical space. These are fine for human engineers, but more comprehensive higher order systems will require new automation techniques yet to be fully exploited. At a number of points in most process synthesis algorithms many alternatives are available. Humans generally make an educated guess and pick one and go on, but rarely return to pursue the implications of selecting another alternative. Computer implementations in principal should be able to pursue and keep track of many more (but not necessarily all) alternatives, with the obvious advantage of potentially discovering a hidden superior design. The systematic generation approach to process synthesis is highly combinatorial. However, extensive computing resources are now readily available. Improved computer-manipulatable representations will likely be developed, as likely will improved computer algorithms, possibly autonomous agents, capable of better generating process alternatives based on such representations. More extensive computerized implementation will be a characteristic of the most effective future process synthesis methods and tools. A major problem with systematic generation approaches, especially human-implemented methods, is the inability to select judiciously among alternative at decision points throughout the algorithm. Try as we might, there are just too many competing factors to enable any kind of reasonable evaluation of open-ended, partially synthesized process design. It is quite difficult to accurately rank all the impacts among decision points such that only the path to the superior final design is identified. As experience with a method is gained, better decisions can be identified most of the time. But there are no guarantees. This is why it is so important to go back and explore the consequences (and economics) of other alternative choices at each stage of the systematic generation paradigm. Traditional evaluation methods often fail to deal effectively with the often combinatorially prohibitive number of alternatives to evaluate. This shortcoming of pure systematic generation algorithms leads us to our next topic. 3.3. Superstructure optimization Superstructure optimization has long been proposed as a process synthesis approach. The structure of a process design (i.e., equipment identity and connectivity) as well as all the design and operating parameters for each piece of equipment can all be determined optimally and simultaneously. Theoretically the superstructure initially encompasses many redundant paths and equipment alternatives for achieving the design objectives. Superstructure optimization is the process


of stripping away the superfluous paths and equipment alternatives to find the “best” solution. The material flow through each interconnection, as well as scale, operating conditions, and other design parameters for each piece of equipment are then determined in one enormous simultaneous mathematical program by optimization of a desired performance criterion. A typical design criterion is net present cost. If at the optimum solution the flow through some interconnection, or the size of a corresponding piece of equipment is zero, then the associated pathway is deleted from the flow sheet. In this fashion both the design structure and other design parameters are optimized simultaneously. Of course true optimization can only be achieved if the optimal process pathway was embedded within the original superstructure. Two separate and distinct problems still limit the use of superstructure optimization techniques: (1) how to generate the initial superstructure while guaranteeing it contains the “best” solution; (2) how to solve the large optimization problem inherent in practical synthesis problems. Early work in this field showed that superstructure optimization involves an extremely difficult mathematical programming problem for even simple chemical process design problems. Critics pointed out the undifferentiable, discontinuous, and nonconvex nature of the resulting mixed-integer nonlinear program, not to mention the lack of methods for generating good, but not uselessly complex superstructures. In any event, neither computer software nor hardware were up to the task except for extremely simplified subproblems. However, over the last decade steady progress has been made attacking each of these mathematical difficulties resulting in the development of a new kind of optimization technique, generalized disjunctive programming (Yeomans & Grossmann, 1999). This advance, along with the ready availability of much greater computing resources, now makes the superstructure optimization approach potentially practical, but yet to be realized on usefully complex synthesis problems. What about the problem of superstructure generation? This brings us full circle to our previous topic of systematic generation. In the future, superstructures may be generated by following all or at least some of the most promising alternative decisions at each stage of the systematic generation process. The resulting flow sheets then could be combined into an initial superstructure. This will become especially practical as advanced computerized methods for systematic generation are implemented. Although the problem size will be very large, it is believed that superstructure optimization capabilities will be up to the task. 3.4. Changing performance criteria Process designs have always been evaluated from a number of different viewpoints including, of course, economics, but also health and safety, environmental impact, energy consumption, controllability, flexibility, ease of construction and maintainability. It is very likely that even more social factors

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may become important in the future, including sustainability, life cycle impact, atom economy, climatic impact, labor utilization, risk minimization, and security. In some special cases, competing factors can be reduced to a common denominator, for example costs and benefits, with trade-offs incorporated into an economic optimization objective function. More often the various factors cannot be rationalized and may not be uniquely quantifiable. Most likely design selection will involve multi-criteria optimization and evaluation of Pareto sets. This will require that the synthesis system generate not only one economic optimum design, but rather whole families of designs, particularly involving different chemistries. Each may need to be evaluated from distinct points of view, or with yet-to-be-developed optimization objectives that somehow incorporate social criteria. 3.5. Interaction and integration with other aspects of process invention Commercializing a new chemical process is a complicated enterprise involving many steps. In the future, process designers are likely to interact much more closely with other parts of the overall innovation process, both upstream and downstream of the traditional process synthesis step. Consider the issues of process controllability and flexibility. In current practice process flow sheets are evaluated in sequential fashion. They generally are first invented and then the resulting design is analyzed against a number of factors. These include: (1) dynamic behavior; (2) flexibility—ranges of applicable operating conditions, specifications, and turn-down/turn-up ratios; (3) robustness—tolerance toward changes in raw material quality and other process upsets; and, (4) controllability—the ability to consistently produce in-specification product despite all these disturbances. Typically control schemes are designed after the process is synthesized and optimized. In the future, operability and flexibility considerations may be integrated into the process synthesis procedures themselves, rather than considered as a subsequent step. Moreover at the present time, process chemistries first are invented and then process designs are synthesized to implement these chemistries. Process chemistry involves invention and refinement of the synthetic sequence by determination of reaction conditions believed to be important such as required catalysts, temperatures, concentrations, purities, and solvent needs. Clearly process chemistry, and especially catalysis, has the greatest influence on the potential advantage of a process technology and especially impacts many of the evolving social considerations. It is generally only after these parameters largely have been fixed that process design engineers begin their work. Too often important chemistry-related parameters are set without optimization before the flow sheet is created, and then not challenged sufficiently. The result is often sub-optimal design. With intense competition in global markets, rapid, efficient, cost-effective synthesis, development, and implementation of new chemistries and

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processes will become increasingly critical. Several advances are on the horizon that will materially impact this cycle time dilemma. The proven utility of simple group contribution models such as UNIFAC have laid the foundation for even more elaborate and effective second order predictive structure–activity relationship models. With increasing computational power available and improving predictive methods, computational chemistry is now virtually capable of providing much more reliable reactivity predictions. We are just beginning to see the quantum increase in catalysis development productivity achievable by combinatorial chemistry and rapid throughput experimentation techniques. In the future, it is anticipated that process chemistry and process engineering will be integrated much more tightly. Process engineering considerations will have a greater impact on process chemistry decisions at a much earlier stage. Rapid feedback between the functions will be commonplace. This feedback will be enabled by concomitant advances in computational chemistry, combinatorial and high-throughput chemistry, enhanced physical property predictive methods, process modeling, as well as by the process synthesis breakthroughs we have discussed above. In the not too-distant future virtual chemistry experiments coupled with automated process synthesis and effective process modeling, may reduce the role of costly and time-consuming research and piloting operations. This integrated approach holds out the promise of a real competitive edge to those who have the skill to take advantage of them.

4. Conclusions Chemical process synthesis methods and tools developed over the last several decades have reached a modest level of maturity that nevertheless have provided an advantage to practitioners in an environment of increased costs and shrinking margins. It is believed a new surge in demand for products from the processing industries may be underway, especially in the developing world. However, this growth is likely to take place in an environment of even keener competition and greater concern for additional factors such as raw material and energy availability, climate change mitigation, sustainability, and inherent security. Systematic tools will be even more important than today as an aid to inventing advantaged process designs. The future will probably see an expanded role for the systematic generation synthesis paradigm for both overall process design and that for specific subsystems such as reaction, separation, energy, environment, control, and the like. Advances from artificial intelligence may inspire new algorithms for process synthesis incorporating new

representations of the underlying physical sciences, new engineering art, new social concerns, new design strategies, and new computerized implementations. The future may also see a merging of the systematic generation and superstructure optimization paradigms in which following the consequences of alternative decisions within the systematic generation paradigm leads to the superstructure whose discrete and continuous variables may be simultaneously optimized by generalized disjunctive programming or some successor technique. And no matter how complex the objective function, the resulting process designs will certainly be evaluated from additional points of view. Therefore, the superstructure optimization will likely need to produce families of good designs for additional multi-criteria Pareto optimization. Finally, future process synthesis methods are likely to involve a greater degree of interaction with other parts of the process innovation enterprise including in particular process and catalytic chemistry on one hand and operability and control expertise on the other. Overall, the need for systematic process synthesis methods and tools has never been greater. There are many challenges. But we are excited and optimistic that continued progress will be made and that these challenges will be met.

References Barnicki, S. D., & Siirola, J. J. (1997). Separation process synthesis. Kirk-Othmer encyclopedia of chemical technology, John Wiley & Sons, Inc., New York (4th ed., Vol. 21, p. 923). Barnicki, S. D., & Siirola, J. J. (2001). Systematic chemical process synthesis. Formal engineering design synthesis (p. 362). Cambridge: Cambridge University Press. Doherty, M. F., & Malone, M. F. (2001). Conceptual design of distillation systems (p. 183). New York: McGraw-Hill Higher Education. Kirkwood, R. L., Locke, M. H., & Douglas, J. M. (1988). A prototype expert system for synthesizing chemical process flowsheets. Computers and Chemical Engineering, 12, 329. Mahalec, V., & Motard, R. L. (1977). Procedures for the initial design of chemical processing systems. Computers and Chemical Engineering, 1, 57. Siirola, J. J. (1995). An industrial perspective on process synthesis. Foundations of computer aided process design (Vol. 91, p. 222). American Institute of Chemical Engineers Symposium Series No. 304. Siirola, J. J. (1996a). Industrial applications of chemical process synthesis. Advances in chemical engineering (Vol. 23, p. 1). New York: Academic Press. Siirola, J. J. (1996b). Strategic process synthesis: Advances in the hierarchical approach. Computers and Chemical Engineering, 20, S1637. Siirola, J. J., & Rudd, D. F. (1971). Computer-aided synthesis of chemical process designs. Industrial and Engineering Chemistry Fundamentals, 10, 353. Yeomans, H., & Grossmann, I. E. (1999). A systematic modeling framework of superstructure optimization in process synthesis. Computers and Chemical Engineering, 23, 709.