On Wednesday, September 11, 2019, Prof. Yuri A.W. Shardt (TU Ilmenau, Germany) gave a lecture on "Big Data and System Identification: Challenges and Opportunities".
Abstract: With the recent demands on industry to improve their environmental, safety, and profit levels, industry has started to focus strongly on process monitoring in order to maintain the process at its optimal conditions. One large issue is the availability of information upon which to base the process monitoring. In many cases, the required information can be missing, unreliable, or hard-to-measure. One approach to resolving this problem is through the development and implementation of soft sensors. Soft sensors are a mathematical model that takes all available information and seeks to make a forecast for the requested value. Soft sensors consist of two parts: a model of the process and a bias update term. The process model provides an estimate of the forecast value, while the bias update term corrects for any offset present. This presentation will provide an overview of the framework for developing and implementing soft sensors, as well as discussing some common problems. The key results will be illustrated using two examples drawn from the hot steel rolling mill and the bitumen extraction processes.
Bio: Prof. Dr. Yuri A.W. Shardt is, since September 2017, the chair
of the Department of Automation Engineering at the Technical University
of Ilmenau, Germany, working on
the development of advanced system identification and fault detection and isolation
methods for application to industrial problems. He is teaching courses in statistics and system identification. He has worked at the University of Waterloo, the University of Duisburg-Essen on the Alexander von Humboldt Fellow, in the ceramics and glass-making industry, and at the University of Alberta. In these jobs, his research focused on the development and implementation of advanced control methods for complex and uncertain systems.