Process analysis is a great challenge in industry due to the complexity of industrial production. In the present work, an approach was developed based on online near-infrared spectroscopy and alternating trilinear decomposition (ATLD) method for industrial process analysis. The basic idea of the approach is to extract the common information that represents the common property of the batches using ATLD. Using common information, the production process can be monitored by investigating the variation of the common property, and quality assurance can be achieved by discrimination analysis. Taking the tobacco production as an example, the results show that the method is able to capture the intrinsic information of the products and performs well in process analysis and quality assurance.