Abstract: In order to enhance the sustainable competitiveness of light industry equipment manufacturing industry in the process of green development, based on the concept of critical to green quality characteristics (CTGQs), a CTGQs extraction model is established to identify the process parameters that have the greatest impact on the environment, The critical to green quality characteristics extraction of light industry equipment in manufacturing stage is realized. In order to eliminate the redundant data in the extraction process, the improved ReliefF algorithm is combined with adaptive particle swarm optimization (APSO) algorithm to improve the accuracy of CTGQs extraction. Finally, a beer fermentation tank is taken as an example to verify the effectiveness of the model.