Prediction of machine production state based on Bayesian Network

Inhalt:
Aiming at the problem of machine production state prediction in the process of workshop task processing, from the perspective of the correlation between various production states, taking the aluminizing machine required in a flexible workshop as the research object, and based on its production state index data, Bayesian Network (BN) is introduced into the production state prediction of the aluminizing machine. Through BN structure learning and parameter learning, some production states of aluminum plating machine are inferred and predicted. The results show that BN can effectively reflect the correlation between the production states of aluminum plating machine, and can reveal the key factors affecting any production state, to provide a basis for the management of subsequent production links.