As an important part of automobile transmission device, the machining quality of synchronizer tooth hub has a direct impact on the performance and reliability of the transmission. Aiming at the problem of low efficiency in judging the range of tooth hub error source by manual experience, this paper proposed an error tracing method based on bat algorithm to optimize BP neural network. The error sources in the tooth hub machining process were analyzed, and the bat algorithm was used to optimize the weights and thresholds. The BA-BP error tracing model was constructed after obtaining the optimal value, data samples were collected to verify the model and compared with the error traceability method of BP neural network before optimization. Compared with the accuracy of the BP neural network traceability model before the optimization was 83.56%, the optimized accuracy was 96.34%, which significantly improved the traceability accuracy，this method allows the production personnel to trace the error causes of the subsequent out-of-tolerance workpieces, which is convenient to directly deal with and eliminate the problems in the production process, so as to improve the production efficiency.