A high level of monitoring is necessary for the safety and product quality of the electrical fused magnesia furnace (EFMF). In this paper, a monitoring method based on latent subspace for EFMF is proposed to fully mine the effective information of multi-source heterogeneous data in the process. By minimizing the distance of different types of data in the subspace, the corresponding projection matrix is obtained. Then the data is projected into the obtained subspace to estimate whether fault occurs.In summary, the main contributions of this paper are threefold.