A brief history of pinch technology

In 2005, a colleague from Malaysia gave me an odd Christmas gift — a photocopy of an obscure doctoral thesis on industrial energy conservation using heat exchange networks by Charles Hohmann dating back to 1971. This document, with its typewritten text and painstakingly hand-drawn figures, was a treasure of sorts, a lost document in the field of pinch analysis and process integration. Although the value of the methodology described in the work is quite evident in hindsight, especially considering today’s inflated energy costs, Hohmann’s work predated the oil crises of the 1970s and went largely unappreciated by his peers. Apparently, he eventually abandoned the field and moved on to other interests. It wasn’t until the work of Linnhoff in the late 1970s and early 1980s that pinch analysis hit the mainstream. Linnhoff himself eventually left academia to co-found Linnhoff March, which is now an international engineering firm that runs a thriving global business built on services and products that use pinch analysis. One of the lessons here is that in R&D, luck and timing are critical. Hohmann’s story is echoed by the experience of one of my colleagues in La Salle, who did his master’s thesis under one of Linnhoff’s academic "descendants" in 1990. He, too, abandoned pinch analysis for bioprocessing, although today he still lectures on the topic to our undergraduate and graduate students.

What exactly is pinch analysis? The term refers to a family of computing techniques that aid in designing system networks or cascades. Proper design of such networks is essential for efficient use of resources, such as fuel, water, time, money or even human resources. In the early days before the emergence of the ubiquitous PC, such pinch analysis made use of graphical displays that use angles and distances as surrogates for various physical quantities. A skilled practitioner can turn a pencil, ruler and several sheets of graphing paper into a crude analog computer that can solve pretty complex design problems. However, such feats are nowadays more notable for their intuitive appeal or mathematical elegance, rather than their necessity. I, for one, find it simpler to formulate mathematical models, and then write programs to solve them. This preference represents a different school of thought which offers the advantage of being able to solve a wider array of design problems, and in that sense is the "better" way, but I’m sure pinch advocates can make equally convincing arguments otherwise. Several months ago, Robin Smith of UMIST gave a lecture in Kuala Lumpur on the possible future of this area of research — the fusion of the pinch analysis and mathematical modeling schools of thought into a single unified framework. It remains to be seen whether his predictions will pan out; I encourage any interested researchers to give it a try. In the meantime, for my lectures, I use the term "process integration" rather than "pinch analysis," as I find it more encompassing of various approaches. In contrast, one can argue that pinch analysis refers merely to a subset of techniques under the more general umbrella of process integration.

After early applications in energy conservation matured and reached commercial level, there emerged a whole gamut of other applications of pinch analysis to other areas. It is significant that many of the new applications were developed through analogies (on this topic, I always like to quote Richard Dawkins, the renowned evolutionary biologist from Oxford, who once said that the judicious use of analogies is essential for the advancement of science). In the late 1980s, Mahmoud El-Halwagi (and his less famous Ph.D. adviser, Manousiothakis) used pinch analysis to determine how process plants can efficiently use "mass separating agents" such as industrial solvents. About half a decade later, Robin Smith (along with his less famous student, Y.P. Wang) extended the principle of pinch analysis to industrial water conservation. To this day, El-Halwagi (now with Texas A&M) and Smith are recognized internationally as two of the gurus in the field of pinch analysis and process integration. More recent extensions of pinch analysis include work on industrial supply chains by Uday Shenoy, now retired from the Indian Institute of Technology, and exotic applications such as financial planning by Toshko Zhelev at the University of Limerick in Ireland. One of my own recent contributions in this area, done jointly with the aforementioned Malaysian colleague, discusses how pinch analysis can be used in national or regional energy planning with a view to meeting carbon dioxide emission limits. That paper will soon appear in the journal Energy.

Having seen how the field has evolved over the past four decades, we then ask the question: what’s next? New computing methods, perhaps? I have described in a previous column how my students and I have demonstrated the use of swarm intelligence to solve process integration problems. Would Petri nets or cellular automata work as well? What about new applications? For example, could pinch analysis be used to sort out storage difficulties encountered in biofuel supply chains? Could some bright electrical engineer figure out how to use pinch analysis for economic power dispatch problems? To me, the possibilities seem endless. At the same time, I find that this field offers significant opportunities for sufficiently talented and dedicated researchers to do internationally competitive work, even with the financial constraints faced by the typical Philippine university.

I recently recruited a promising Ph.D. student to look into process integration as a possible dissertation topic. To get her started, I handed her a pile of old papers that represent a cross section of the history of this field. I’m hoping that a historical perspective will be what it takes to spark the speculative steps which will be the starting point of a significant body of work on process integration. Whether this will be the case, remains to be seen. But as the experience of Charles Hohmann demonstrates, in research, luck is as much a factor as talent. And so researchers must be willing to gamble on new ideas — because that’s where the future really begins.

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Dr. Raymond R. Tan is an associate professor of the Chemical Engineering Department and researcher exemplar at De La Salle University-Manila. A recipient of multiple awards from the National Academy of Science and Technology, some of his recent works on pinch analysis and process integration can be found in the Journal of Cleaner Production; Computers & Chemical Engineering; Clean Technologies & Environmental Policy; and Energy. For more information, visit his website at http://www.geocities.com/natdnomyar/web or e-mail him at [email protected].