AbstractThis paper provides an overview and analysis of statistical process monitoring methods for fault detection, identification and reconstruction. Several fault detection indices in the literature are analyzed and unified. Fault reconstruction for both sensor and process faults is presented which extends the traditional missing value replacement method. Fault diagnosis methods that have appeared recently are reviewed. The reconstruction‐based approach and the contribution‐based approach are analyzed and compared with simulation and industrial examples. The complementary nature of the reconstruction‐ and contribution‐based approaches is highlighted. An industrial example of polyester film process monitoring is given to demonstrate the power of the contribution‐ and reconstruction‐based approaches in a hierarchical monitoring framework. Finally we demonstrate that the reconstruction‐based framework provides a convenient way for fault analysis, including fault detectability, reconstructability and identifiability conditions, resolving many theoretical issues in process monitoring. Additional topics are summarized at the end of the paper for future investigation. Copyright © 2003 John Wiley & Sons, Ltd.