Discussing the main issues in the treatment and reconciliation of plant data, this text covers the concepts of estimability and redundancy in steady-state processes; process variable classification for linear and nonlinear plant models; the adjustment of measurements for different kinds of plant models; advantages of sequential processing of measurements and constraints; definition and analysis of the data reconciliation problem; analysis of dynamic and quasi-steady-state processes; the problem of joint parameter estimation-data reconciliation; and trends in the field. Case studies are presented in the final chapter. Suitable for graduate students, advanced undergraduates in chemical engineering, and practitioners engaged in the industrial application of reconciliation techniques.