Due to the influence of production environment and operating parameters, the coal slurry flotation process experiences significant fluctuations in operating conditions, leading to a decrease in product quality and even occurrence of abnormal conditions. To address this issue, this paper proposes an integrated safe operation and product quality control method for coal slurry flotation process based on distributed hybrid Bayesian network. Based on the distributed modeling idea, the coal slurry flotation process is deeply analyzed, divided into several interrelated local modules and the corresponding local hybrid Bayesian network model is established. The global hybrid Bayesian network model of coal slurry flotation process is further determined by combining process knowledge and associated variables, which effectively improves the efficiency and accuracy of modeling. The model improves the inference accuracy of control decisions by introducing continuous nodes based on discrete Bayesian networks. When abnormal conditions occur in the coal slurry flotation process, the contribution graph algorithm is used to identify the local modules causing the abnormal conditions. Bayesian inference is then employed to obtain safe operation control decisions, eliminating the abnormal conditions. Furthermore, by combining the simulated annealing algorithm on this basis, product quality control decisions are obtained to improve the coal product quality, achieving an integrated control of safe operation and product quality of the coal slurry flotation process. Finally, the effectiveness of the proposed method is validated through simulation experiments of the coal slurry flotation process.