Description: Dynamic Modeling of Complex Industrial Processes: Data-driven Methods and Application Research Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Chao Shang Format: Paperback Publisher: Springer Verlag, Singapore, Singapore Imprint: Springer Verlag, Singapore ISBN-13: 9789811338892, 978-9811338892 Synopsis This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.
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Book Title: Dynamic Modeling of Complex Industrial Processes: Data-driven ...
Number of Pages: 143 Pages
Language: English
Publication Name: Dynamic Modeling of Complex Industrial Processes: Data-Driven Methods and Application Research
Publisher: Springer Verlag, Singapore
Publication Year: 2019
Subject: Engineering & Technology, Mathematics
Item Height: 235 mm
Item Weight: 261 g
Type: Textbook
Author: Chao Shang
Subject Area: Mechanical Engineering
Series: Springer Theses
Item Width: 155 mm
Format: Paperback