Research On Spare Parts Prediction Of Machine Tool Spindle System Based On Operation Covariate Analysis

CNC machine tools are modern manufacturing equipment,and the stability and reliability of its processing technology will reflect the technical level of a country's manufacturing equipment.CNC machine tools fail during the production process,and due to shortage of spare parts,they cannot be repaired in time,which will bring huge economic losses to the enterprise.However,the storage of spare parts is too large,the production cost of enterprises is increasing,and how to accurately predict the number of spare parts has been a research hotspot and difficulty in the field in recent years.This research relies on the Liaoning Provincial Natural Science and Technology Fund Project “Research on Reliability Evaluation and Spare Parts Prediction Model of CNC Machine Tool Repairable System”.Mainly with a certain type of CNC machine tool as the research object,the specific analysis of the number of spare parts prediction of the machine tool spindle system considering the running covariate.The specific research contents are as follows:First,research and analysis on the structure,working process and working principle of CNC machine tools and machine tool spindle systems.Second,collecting the fault data of the machine tool and screen it,and perform FMEA analysis on the data.The fault data is divided according to the fault location and the fault mode,and the fault location is higher than the fault location and the fault mode,and the weakest link in the whole machine is analyzed.Third,using the meta-action fault tree to perform key spare parts screening on the spindle system,and analyze the top event of the ball screw transmission component in the spindle system,and analyze the importance of each bottom event according to the quantitative calculation of the meta-action fault tree.Then,analyze the components with high participation in the spindle system to complete the screening of key spare parts.Fourth,the fault data and operation covariant factors are quantified,and the correlation analysis of each operation covariant is carried out by SPSS analysis software.According to the covariant regression coefficient value,the number of non-repairable spare parts in a specific period of time is calculated,and then the predicted number of required spare parts is obtained.The results show that the errors of the actual spare parts are within 10% compared with the domestic spare parts and the imported spare parts,which accords with the range of the predicted errors.