基于BP神经网络的制造过程质量诊断模型研究

In order to solve the problem that quality diagnosis needs to be completed by quality personnel when the traditional manufacturing system monitors the state of the manufacturing process.Firstly, this paper designs a quality diagnosis model of manufacturing processbased on BP neural network to realize the basic patterns recognition andabnormal patterns feature parameter estimation of the quality control chart. Then, through Monte Carlo simulation of quality historical sample data to conduct experiments and verify the reliability of the model, the experimental results show that the manufacturing process quality diagnosis model based on BP neural network can meet the needs of modern production. Finally, through the real-time data analysis of the cigarette production process, it is verified that the quality diagnosis model of manufacturing process proposed in this paper can effectively solve the quality diagnosis problems in the actual manufacturing process.