A method for analyzing abnormality of automobile sunroof manufacturing process by using Bayesian method

In the automotive sunroof manufacturing industry, due to factors such as people, machines, materials, manufacturing methods, measurement methods, environmental impacts, etc., many factors affect the quality of the final product, so the traditional control chart diagnosis and analysis is very difficult, in response to this situation, a kind of Abnormal diagnostic method for manufacturing process using Bayesian network. Based on the prior knowledge of process anomaly diagnosis and the abnormal features that need to be diagnosed, a Bayesian network-based manufacturing process anomaly diagnosis model is constructed.