This paper proposes a new fault detection method using an absolute-value based Fisher discriminant analysis combined with the individuals and moving range chart. Two fault identification methods are also proposed by using the discriminant model, those are quantitative data classification method and projected trend analysis. The performance of these methods are evaluated by Tennessee Eastman benchmark problem.