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Data Processing and Reconciliation for Chemical Process Operations
Computer techniques have made online measurements available at every sampling period in a chemical process. However, measurement errors are introduced that require suitable techniques for data reconciliation and improvements in accuracy.
Reconciliation of process data and reliable monitoring are essential to decisions about possible system modifications (optimization and control procedures), analysis of equipment performance, design of the monitoring system itself, and general management planning.
About the Authors
Prof. José A. Romagnoli
The Cain Chair in Process Systems Engineering in the Department of Chemical Engineering and is the director of the Laboratory for Process Systems Engineering at Louisiana State University. He earned a PhD in chemical engineering from the University of Minnesota. Dr. Romagnoli has authored more than 300 international publications and was awarded the Centenary Medal of Australia for his contributions to chemical engineering. His research covers all aspects of process systems engineering, including modeling of complex systems, advanced model-based control, intelligent process monitoring and supervision, and plant-wide optimization.
Prof. Mabel Cristina Sánchez
Prof. Mabel Cristina Sánchez is affiliated with the Planta Piloto de Ingeniería Química (PLAPIQUI) in Bahía Blanca, Argentina, and is a co-author of Data Processing and Reconciliation for Chemical Process Operations. Her work focuses on data reconciliation, process monitoring, and estimation techniques aimed at improving data quality and supporting decision-making in chemical process systems. Her contributions have helped establish key methodologies widely used in both academic research and industrial applications of process systems engineering.