Compared with conventional machine tools,heavy-duty CNC machine tools have the characteristics of complex structure,difficulty in fault tracing,few samples,and insufficient data,which makes it difficult to conduct reliability research on them.Aiming at this problem,the fault data of a certain factory′s TH series of heavy-duty CNC machine tools were analyzed,and the Weibull distribution function was used to establish a reliability model of a certain heavy-duty CNC machine tool.In order to obtain higher fitting accuracy,three methods including least squares linear regression analysis,maximum likelihood estimation and grey model estimation were used to estimate the parameters and select the optimal value.The Weibull distribution model developed by the maximum likelihood estimation method has the smallest fitting error and the highest accuracy,which is proved by the K-S test.Taking the model obtained by the maximum likelihood estimation as the reliability evaluation model,through calculation,the observed value and the estimated value of the point for this series of heavy-duty CNC machine tools are 298.155 0 h and 298.675 9 h respectively,which are basically equal,proving the correctness of the model.