Advances in Data-Driven Modeling, Fault Detection, and Fault Identification

Advances in Data-Driven Modeling, Fault Detection, and Fault Identification: Applications to Chemical Processes presents a comprehensive collection of research focused on data-driven modeling techniques for robust modeling, fault detection, and fault identification in chemical processes. This accessible guide caters to both academic and industrial researchers seeking to enhance their work with data-driven methodologies. The book begins with an overview of key methods, emphasizing their significance in research and industry applications. Chapters delve into various chemical processes, such as the Tennessee Eastman Process and a Fischer-Tropsch bench scale setup, to validate and compare the discussed techniques. The content is organized into three main categories: - Basic and advanced robust empirical techniques- Prominent empirical statistical charts for detecting faults in multivariate systems- Conventional and novel, multiclass classification, machine-learning techniques for accurately distinguishing between different fault types in batch or real-time scenariosWhether a researcher or practitioner, this book is an essential resource for leveraging data-driven approaches in chemical engineering fields.

Dr. Mohamed Nounou is a Professor of Chemical Engineering in the College of Science and Engineering at Hamad Bin Khalifa University (HBKU), in Qatar. Prior to joining HBKU, he was with Texas A&M University at Qatar (TAMUQ) for 18 years. He received his B.S. degree (Magna Cum Laude) from Texas A&M University, College Station in 1995, and his M.S. and Ph.D. degrees from the Ohio State University in 1997 and 2000, respectively, all in chemical engineering. Then, he joined PDF Solutions, Inc. until 2002 when he joined the chemical and petroleum engineering department at the United Arab Emirates University (UAEU). Then, he joined TAMUQ in 2006, where he made significant contributions and received numerous awards at the college and university levels. In teaching, he received the AFS College-level and University-level Distinguished Achievement Teaching Awards in 2011 and 2012, respectively. He also received the "TAMUQ Faculty Excellence Award” in 2013. He later received the "Chemical Engineering Faculty of the Year Award” five times in 2013, 2014, 2016, 2017, 2018, and 2021, and the "Student Government Association CHEN Educator of the Year Award” in 2016. In service, Dr. Nounou was appointed a chair of the "Aggie Life” program, which is a university-wide initiative that aims at enhancing the college life experience of freshman students at TAMUQ. He has been chairing student advising since joining TAMUQ and also chaired the ABET Committee during the first accreditation cycle in 2008, where the Program received full accreditation, and he received a recognition award for this role. He also helped establish a chapter of AIChE at TAMUQ in 2007, and later established and advised the Gamma Delta chapter of the Omega Chi Epsilon honor society at TAMUQ, the first chapter outside the US. As a result, he received the "Student Organization Advisor of the Year Award” in 2014 and 2016. Dr. Nounou is also an accomplished researcher in the area process systems engineering. He received research funding over $5M and published a book and more than 200 journal and conference papers and book chapters. He served as an associated editor for several journals. He is an associate editor for the "Network Modeling Analysis in Health Informatics and Bioinformatics". He is a senior member of AIChE and IEEE.

1. Introduction 2. Modeling 3. Fault detection 4. Fault identification 5. Appendix