Bayesian fault identification of multistage processes

Multistage process fault identification have received much attention recently. In this article, we focus on identifying faults in multistage processes that affect the process mean vector. The new method utilizes Bayesian theory and evaluates the posterior probability of each possible fault scenarios. The scenario associated with the largest posterior probability is identified. Numerical analysis proves that the new method has satisfactory diagnosis power and accuracy.