From the Back Cover

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.