Data is at the very heart of the digital revolution. However, very often industrial big data are dirty, missing or unreliable. Data reconciliation and gross error detection techniques allow handling these shortcomings, making data usable and dependable.
If you are interested in learning more about this topic, join us at this year's AIChE Spring Meeting where we will present an "Application-Oriented Review of Data Reconciliation and Gross Error Detection Methods for Heat Exchanger Networks."