The work aims to achieve fast and accurate optimization of the abrasive blocks during formulation of the barrel finishing process. Based on the analysis of the characteristics of the barrel finishing process, the case base was constructed according to the E-R diagram of the optimization of the abrasive blocks, and the optimal model of the abrasive blocks based on case-based reasoning was established. According to the data types of different case feature attributes, the appropriate feature attribute similarity calculation method was selected. The weight of case feature attribute was determined by the analytic hierarchy process, and the weighted nearest neighbor method was used to calculate the comprehensive similarity between cases. The optimal abrasive block of new problem was obtained by case processing. The fuzzy C-means clustering algorithm was used to deal with redundant cases to realize the dynamic optimization of the case base. Finally, different data of different parts types were used for simulation. The results of a large number of simulation studies demonstrated that the fuzzy C-means clustering algorithm could be used to deal with the redundant cases in the case base, which could effectively improve the retrieval efficiency and accuracy of case-based reasoning. For the actual new problems, based on the model and through case retrieval and correction, similar cases of new problem were quickly extracted from the case base, thus verifying the feasibility and effectiveness of the model. It was important to provide decision guidance for the optimization of the abrasive blocks of the new problem. The case-based reasoning technique based on fuzzy clustering can be used to optimize the abrasive blocks during the implementation of the barrel finishing process.