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Process engineering is the understanding and application of the fundamental principles and laws of nature that allow humans to transform raw material and energy into products that are useful to society, at an industrial level. By taking advantage of the driving forces of nature such as pressure, temperature and concentration gradients, as well as the law of conservation of mass, process engineers can develop methods to synthesize and purify large quantities of desired chemical products. Process engineering focuses on the design, operation, control, optimization and intensification of chemical, physical, and biological processes. Process engineering encompasses a vast range of industries, such as agriculture, automotive, biotechnical, chemical, food, material development, mining, nuclear, petrochemical, pharmaceutical, and software development. The application of systematic computer-based methods to process engineering is "process systems engineering".
Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s. In recent years it has also been used in power system balancing models and in power electronics. Model predictive controllers rely on dynamic models of the process, most often linear empirical models obtained by system identification. The main advantage of MPC is the fact that it allows the current timeslot to be optimized, while keeping future timeslots in account. This is achieved by optimizing a finite time-horizon, but only implementing the current timeslot and then optimizing again, repeatedly, thus differing from a linear–quadratic regulator (LQR). Also MPC has the ability to anticipate future events and can take control actions accordingly. PID controllers do not have this predictive ability. MPC is nearly universally implemented as a digital control, although there is research into achieving faster response times with specially designed analog circuitry.
Hsiang-Tsung Kung is a Taiwanese-born American computer scientist. He is the William H. Gates professor of computer science at Harvard University. His early research in parallel computing produced the systolic array in 1979, which has since become a core computational component of hardware accelerators for artificial intelligence, including Google's Tensor Processing Unit (TPU). Similarly, he proposed optimistic concurrency control in 1981, now a key principle in memory and database transaction systems, including MySQL, Apache CouchDB, Google's App Engine, and Ruby on Rails. He remains an active researcher, with ongoing contributions to computational complexity theory, hardware design, parallel computing, routing, wireless communication, signal processing, and artificial intelligence.
IPOPT, short for "Interior Point OPTimizer, pronounced I-P-Opt", is a software library for large scale nonlinear optimization of continuous systems.
John Emory Dennis, Jr. is an American mathematician who has made major contributions in mathematical optimization. Dennis is currently a Noah Harding professor emeritus and research professor in the department of computational and applied mathematics at Rice University in Houston, Texas. His research interests include optimization in engineering design. He is the founder and editor-in-chief of the SIAM Journal on Optimization. In 2010, he was elected a Fellow of the Society for Industrial and Applied Mathematics.
Randal E. Bryant is an American computer scientist and academic noted for his research on formally verifying digital hardware and software. Bryant has been a faculty member at Carnegie Mellon University since 1984. He served as the Dean of the School of Computer Science (SCS) at Carnegie Mellon from 2004 to 2014. Dr. Bryant retired and became a Founders University Professor Emeritus on June 30, 2020.
ASCEND is an open source, mathematical modelling chemical process modelling system developed at Carnegie Mellon University since late 1978. ASCEND is an acronym which stands for Advanced System for Computations in Engineering Design. Its main uses have been in the field of chemical process modelling although its capabilities are general.
Gary Lee Miller is a professor of Computer Science at Carnegie Mellon University, Pittsburgh, United States. In 2003 he won the ACM Paris Kanellakis Award for the Miller–Rabin primality test. He was made an ACM Fellow in 2002 and won the Knuth Prize in 2013.
Dimitri Panteli Bertsekas is an applied mathematician, electrical engineer, and computer scientist, a McAfee Professor at the Department of Electrical Engineering and Computer Science in School of Engineering at the Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, and also a Fulton Professor of Computational Decision Making at Arizona State University, Tempe.
Fred Glover is Chief Scientific Officer of Entanglement, Inc., USA, in charge of algorithmic design and strategic planning for applications of combinatorial optimization in quantum computing. He also holds the title of Distinguished University Professor, Emeritus, at the University of Colorado, Boulder, associated with the College of Engineering and Applied Science and the Leeds School of Business. He is known for his innovations in the area of metaheuristics including the computer-based optimization methodology of Tabu search an adaptive memory programming algorithm for mathematical optimization, and the associated evolutionary Scatter Search and Path Relinking algorithms.
Robert J. Vanderbei is an American mathematician and Emeritus Professor in the Department of Operations Research and Financial Engineering at Princeton University.
Guy Edward Blelloch is a professor of computer science at Carnegie Mellon University. He is known for his work in parallel algorithms.
AIMMS is a prescriptive analytics software company with offices in the Netherlands, United States and Singapore.
Efstratios N. (Stratos) Pistikopoulos is a distinguished research professor at the Department of Chemical Engineering at Texas A&M University, as well as the director of the Texas A&M Energy Institute. From 1991-2015, he was a professor for chemical engineering at Imperial College, where he pioneered multi-parametric programming and invented the concept of explicit or multi-parametric model predictive control. He has authored and co/authored more than 350 peer reviewed journal articles, authored and/or edited 9 books and has been an invited speaker to many academic conferences and lectures, including the 21st Professor Roger W. H. Sargent lecture at Imperial College London entitled "Multi-Parametric Programming & Control 25 years later: what is next?". Additionally, Pistikopoulos has been elected a fellow of the Royal Academy of Engineering in 2013.
Christine A. Shoemaker joined the Department of Industrial Systems Engineering & Management and the Department of Civil and Environmental Engineering as NUS Distinguished Professor on 31 August 2015. Prof Shoemaker obtained her Ph.D. in mathematics from the University of Southern California supervised by Richard Bellman in Dynamic Programming. Upon her graduation, she joined the School of Civil and Environmental Engineering and later the School of Operations Research and Information Engineering at Cornell University, Ithaca, NY, USA. She was promoted to full Professor in 1985. From 1985 to 1988, Professor Shoemaker was the Chair of the Department of Environmental Engineering at Cornell University. In 2002 Prof. Shoemaker was appointed the Joseph P. Ripley Professor of Engineering at Cornell University, USA. In 2015, Prof. Shoemaker became Distinguished Professor at National University of Singapore, in both Industrial Systems Engineering and Management Department and Civil and Environmental Engineering Department. While in Singapore she has worked with Singapore water agency to apply her global optimization algorithms to improve the selection of parameters for computationally expensive partial differential equation models for lake hydrodynamics and complex multi-species water quality elements. These results used her group's new parallel algorithms.
Jorge Nocedal is an applied mathematician, computer scientist and the Walter P. Murphy professor at Northwestern University who in 2017 received the John Von Neumann Theory Prize. He was elected a member of the National Academy of Engineering in 2020.
Gabriela Hug-Glanzmann is a Swiss electrical engineer and an associate professor and Principal Investigator of the Power Systems Laboratory at the Swiss Federal Institute of Technology (ETH) Zürich within the Department of Information Technology and Electrical Engineering. Hug studies the control and optimization of electrical power systems with a focus on sustainable energy.
Ignacio E. Grossmann is an American chemical engineer. He is the R. R. Dean University Professor in the department of chemical engineering at Carnegie Mellon University. Grossmann received his B.S. degree from Universidad Iberoamericana in Mexico City in 1974. He did his M.S. and Ph.D. at Imperial College London with Roger W. H. Sargent in 1975 and 1977 respectively. In 2015 he was the first recipient of the Sargent Medal of the Institution of Chemical Engineers, named in honor of his doctoral advisor.
Lawrence Pileggi is the Coraluppi Head and Tanoto Professor of Electrical and Computer Engineering at Carnegie Mellon University. He is a specialist in the automation of integrated circuits, and developing software tools for the optimization of power grids. Pileggi's research has been cited thousands of times in engineering papers.
References
- ↑ "Lorenz T. Beigler". Carnegie Mellon University. Retrieved January 19, 2021.
- ↑ "History of CAPD". CAPD - Center for Advanced Process Decision-Making. Carnegie Mellon University. Retrieved October 4, 2020.
- ↑ "Lorenz T. Beigler". Informs. Retrieved October 4, 2020.
- ↑ "Computing in Chemical Engineering Award". AICHE. Retrieved January 19, 2021.
