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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
Ebook for Data Processing and Reconciliation for Chemical Process Operations (Volume 2) (Process Systems Engineering, Volume 2) is an fantastic research overview that goes above and beyond what is commonly expected. The meticulous building of this resource, which integrates intellectual understandings with useful strategies to examination preparation, makes it an incredibly useful tool for trainees. This manual, which was created by $_authors$, that are well-regarded academics in their corresponding fields, and released by $_publisher$ on $_publish_date$, is an important resource for any person who is pursuing attaining success in Test bank, Solution manual.
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
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