This paper identifies risk factors in the smart supply chain and develops a risk assessment index system for reducing potential losses in intelligent manufacturing. Specifically, based on the supply chain operation reference theory, we investigate the performance indicators and characteristics of the smart supply chain in intelligent manufacturing in China. A conceptual model for identifying risks of the smart supply chain is developed, and a questionnaire is designed to measure the risks of the smart supply chain in intelligent manufacturing. Using the hierarchical clustering analysis, an improved risk assessment model is derived with 22 risk factors based on 814 valid sample data. Moreover, the information entropy weight method is used to compute the risk weights for the smart supply chain in intelligent manufacturing. The risk weights are further verified by simulation and proved that these risk factors and risk weights have high practical efficiency. Theoretical and practical implications are also presented.