Many industrial process variables have characteristics of high-dimension and not strictly obeying the Gaussian distribution. A method was proposed to solve these problems of the industrial process. The method was based on LTSA algorithm and combined index to improve monitoring performance. Firstly

the local tangent space alignment (LTSA) algorithm was used to get the sub-manifold of low dimension from the normal sample data to achieve dimensionality reduction. The two-step strategy was used to get the new statistical model. Then

the non-Gaussian statistical value and the Gaussian statistical value were constructed. Therefore

the new statistical value weighted by these two statistical values was intended to achieve monitoring of the process. Finally

the proposed method was applied to the Tennessee Eastman (TE) process and the ethylene cracking furnace to demonstrate its effectiveness.