Research On The Reliability Distribution And Prediction Method Of Servo Power Tool-rest Based On The Influence Of Failure

The numerical control machine tool has the pivotal function in the realization modernization road and the national economy.In the whole life cycle of a product,the decisive influence on the reliability level is the design stage.In the process of mechanical design,uncertainty is unavoidable,reliability distribution and prediction is the main method of reliability.At present,although reliability design related work has been carried out in most enterprises,due to the lack of fault data,many tool rest enterprises have not carried out effective reliability allocation and prediction.In this paper,the distribution and prediction of the reliability of the servo-powered tool rest are studied by using the grey theory and the mould theory,combined with the failure data,the method of reliability distribution of Servo power tool rest based on grey theory and the method of reliability prediction of Servo power tool rest based on dynamic weight and mould theory are presented,the main findings are as follows:1.Structure and FMECA analysis of servo-powered tool rest.The function block diagram of the sub-system and the function block diagram of the parts are established for the s * * D series Servo power tool rest.Based on the fault data of the whole machine factory and the tool rest factory in the past five years,the FMECA method is used to obtain all possible fault modes,causes and properties.The code table corresponding to the fault mode of the Servo power tool carrier subsystem and the fault frequency table are compiled,and the relative value of the damage degree of each subsystem is obtained by combining the Quantitative analysis and qualitative analysis,the fault data base is provided for the distribution and forecast expansion in the following paper.2.Reliability allocation for servo-powered tool rest.According to the actual situation,the seven influencing factors of the servo power tool rest are determined,an evaluation table is set up,and according to the evaluation table of each subsystem,an evaluation matrix is set up,finally,the weight information among the evaluation factors is given,and the reliability distribution weight of each subsystem is finally obtained by combining the real fault data with the improved grey theory,then the fault rate assigned by each subsystem is obtained,and compared with the traditional method,the method is more suitable for the reliability allocation of Servo power tool rest.3.Reliability prediction for servo-powered tool rest.Firstly,the traditional expert weight is dynamically processed to get more accurate weight information of each subsystem,and the seven influence factors of the servo power tool rest are processed to get the centroid value,combined with the real fault data,the final evaluation Coefficient is obtained,and the reliability prediction results of each subsystem and Servo power tool rest are determined.4.Application of reliability allocation and prediction software.The interactive interface between reliability allocation and prediction of Servo power tool rest is compiled by using Matlab Gui,and the data is processed by using Matlab program,including the relevant operations of allocation and prediction,and the final result of allocation and prediction is obtained,the software is efficient,simple and easy to operate in reliability allocation and prediction,and the algorithm is applied in engineering.The reliability allocation method of grey theory based on real fault data is used to allocate the reliability of a certain type of servo power turret.The allocation result is easy to find its weak subsystem,which is of great significance to improve the reliability of servo power turret,and also provides a reference for the reliability allocation method of electromechanical hydraulic integrated products.The reliability prediction method based on dynamic weight and fuzzy theory can effectively deal with the influence of uncertain factors such as fault data and imperfect subjective factors on reliability prediction.It is a new reliability prediction method suitable for electromechanical and hydraulic integrated products such as servo power turret.