Advances in Data-Driven Modeling, Fault Detection, and Fault Identification: Applications to Chemical Processes is an accumulation of research on data-driven modeling techniques, and their application towards robust modeling, fault detection and fault identification. The book covers a wide range of basic to advanced empirical techniques in comprehensive detail, and provides a easyto-read guide for academic or industrial researchers that are interested in applying these techniques towards their respective fields. The book starts with exposing the scope of the book, in addition to a brief rundown of the methods discussed, and their importance to academic research and industrial applications. It will also describe some of the chemical processes that will be used to validate and compare the various data-driven techniques, which include the Tennessee Eastman Process and a Fischer-Tropsch bench scale setup. It discusses a first category of the methods, that covers basic and advanced robust empirical techniques, followed by a second category of the methods discussed, that covers prominent empirical statistical charts used to detect faults in multivariate systems, and finally a third category of the methods, that covers conventional and novel multiclass classification machine learning techniques that can be used to accurately differentiate in batch or real-time between different fault classes in industrial process or academic applications.
Mohamed N. Nounou Professor of Chemical Engineering, Texas A&M University, Qatar.
Mohamed Nounou is a professor of Chemical Engineering at Texas A&M University-Qatar. He received the B.S. degree (Magna Cum Laude) from Texas A&M University, College Station, in 1995, and the M.S. and Ph.D. degrees from the Ohio State University, Columbus, in 1997 and 2000, respectively, all in chemical engineering. From 2000 to 2002, he was with PDF Solutions, a consulting company for the semiconductor industry, in San Jose, CA. In 2002, he joined the Department of Chemical and Petroleum Engineering at the United Arab Emirates University. In 2006, he joined the Chemical Engineering Program at Texas A&M University at Qatar, where he is currently a professor. He has received research funding over $5M and published more than 190 refereed journal and conference papers and book chapters. He also served as an associate editor and in technical committees of several international journals and conferences. His research interests include process modeling, monitoring, estimation, system biology, and intelligent control. He is a senior member of the American Institute of Chemical Engineers (AIChE) and a senior member of the Institute of Electrical and Electronics Engineers (IEEE).
Hazem N. Nounou Professor, Electrical and Computer Engineering Program and Assistant Dean for Academic and Student Services, Texas A&M University, Qatar.
Hazem N. Nounou is the Associate Dean for Academic and Student Services and Professor of Electrical and Computer Engineering at Texas A&M University at Qatar. He received the B.S. degree (magna cum laude) from Texas A&M University, College Station, in 1995, and the M.S. and Ph.D. degrees from Ohio State University, Columbus, in 1997 and 2000, respectively, all in electrical engineering. In 2001, he was a Development Engineer for PDF Solutions, a consulting firm for the semiconductor industry, in San Jose, CA. Then, in 2001, he joined the Department of Electrical Engineering at King Fahd University of Petroleum and Minerals in Dhahran, Saudi Arabia, as an Assistant Professor. In 2002, he moved to the Department of Electrical Engineering, United Arab Emirates University, Al-Ain, UAE. In 2007, he joined the Electrical and Computer Engineering Program at Texas A&M University at Qatar, Doha, Qatar. He was the holder of Itochu Professorship from 2015-2017. He published more than 200 refereed journal and conference papers and book chapters. He served as an Associate Editor and in technical committees of several international journals and conferences. His research interests include data-based control, intelligent and adaptive control, control of time-delay systems, system biology, and system identification and estimation. Dr. Nounou is a senior member of IEEE.
Nour Basha Texas A&M University at Qatar, Education City, Doha, Qatar.
Nour Basha is a chemical engineering PhD student at Texas A&M University at Qatar (TAMUQ), with a B.Sc. in electrical engineering and a M.Sc. degree in chemical engineering from the same university. Research interests include process modeling and monitoring, fault detection, data classification, and fuzzy control.
Byanne Malluhi Texas A&M University, Qatar.
Byanne is a chemical engineering Ph.D. student at Texas A&M University at Qatar, with B.S. and M.Sc. degrees in chemical engineering, all from TAMUQ. She briefly worked as an associate process engineer in McDermott from Oct 2019 to May 2020. Her research interests in the process system engineering field include process modeling, monitoring, control, and data analytics.
