A Logistic regression and Autoregressive Moving Average(ARMA)model-based approach to process alarm event prognosis is explicitly introduced in this paper.A sequence of process alarm events which includes states and duration of the alarm events can be extracted from historical data before establishing corresponding Logistic regression and ARMA models

thereby well predicting the process alarm events.A numerical example as well as industrial process data is employed to validate the effectiveness of the proposed methods.