Product quality modeling and optimizing control of soft capsule dropping pills based on LSSVM and PSO

Soft capsule dropping pills product quality control system is a multi-input and multi-output complex system. First of all, the process parameters and a two-level hierarchy index system of soft capsule pills product quality were proposed based on the analysis to the production process. Then the model was established based on least squares support vector machine (LSSVM), whose inputs are the process parameters and outputs are the secondary quality indexes. Analysis hierarchy process (AHP) was used to determine the weights of the secondary quality indexes. On this basis, particle swarm optimization (PSO) algorithm was used to optimize the process parameters in order to improve the yield of soft capsule pills, which is a multi-objective optimization problem. The nominal values of the process parameters corresponding to the highest yield can be obtained. The yield increases by 2.7% when the optimizing parameters are used to the soft capsule dropping pills process.