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. While the reconciliation of the process data has been studied for more than 20 years, there is no single source providing a unified approach to the area with instructions on implementation. Data Processing and Reconciliation for Chemical Process Operations is that source. Competitiveness on the world market as well as increasingly stringent environmental and product safety regulations have increased the need for the chemical industry to introduce such fast and low cost improvements in process operations.
* Introduces the first unified approach to this important field
* Bridges theory and practice through numerous worked examples and industrial case studies
* Provides a highly readable account of all aspects of data classification and reconciliation
* Presents the reader with material, problems, and directions for further study
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Routinely collected sensor data provide the first level of information for use in ensuring the optimal and safe operation of manufacturing plants. However, these numerical observations are seldom consistent, as they may be corrupted by measurement errors as well as by random and gross errors regardless of how well the instrumentation system is designed and operated. Erroneous data may compromise plant safety and lead to off-specification production.
Although the reconciliation of process data has been studied for more than 20 years, Data Processing and Reconciliation for Chemical Process Operations provides the first unified treatment of this important subject. An introduction to the modern literature is presented together with in-depth coverage of the relevant theory of data reconciliation. The theory is illuminated by numerous examples from representative chemical processes, including detailed industrial case studies.
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Book Description Elsevier. Book Condition: New. pp. 270. Bookseller Inventory # 8348715
Book Description Academic Press, 1999. Hardcover. Book Condition: New. Bookseller Inventory # P110125944608
Book Description Academic Press, 1999. Hardcover. Book Condition: New. Bookseller Inventory # DADAX0125944608
Book Description Academic Press, 1999. Hardcover. Book Condition: New. book. Bookseller Inventory # 0125944608