Reliability Modeling And Assessment Of The Cutting Tool For Milling Difficult-to-Machine Materials

‘Special achievements of numerical control machine tool should be intensively applied to the fields such as aerospace,automobile,machine tool,etc.Domestic CNC(Computer Numerical Control)system,functional parts and the cutting tools should be promoted comprehensively in research,development and assorted applications.And finally the machine tool gets to be intelligent’ are clearly proposed in the report of ‘Made in China 2025’.The reliability of the cutting tool as a key part of CNC is one of the most important representations for the machining efficiency and the stability,so carrying out the research on reliability assessment of the cutting tool has significant value in both theoretical and engineering aspects.Reliability assessment of the cutting tool needs degradation data.In order to obtain the degradation data,the cutting tool maching experiments are carried out in this study.However,it is difficult to get enough experimental data due to the limitations in many aspects such as processing condition,cost and live environment,etc.Aimed at the challenges ‘small sample,few data’ in the cutting tool maching experiments,Bayesian method is used in this study to fuse information.The research on the reliability assessment of the cutting tool will carry out based on the theory,and the detailed research information mainly includes the following three aspects:(1)In order to obtain the reliability value of the cutting tool in a fixed time,a reliability assessment method of the cutting tool is proposed based on the model of degradation distribution.The reliability value of the cutting tool in a fixed time is calculated with the distribution of degradation data and Bayesian method.After that,the failure distribution and failure characteristics of the cutting tool are analysed in this work.The change trend of reliability of the cutting tool with time is achieved.(2)In order to obtain the degradation process of the cutting tool,this thesis proposes a reliability assessment method based on stochastic process model.Without considering the diversity of degradation process of the cutting tool,the parameters in the performance degradation model of the cutting tool are updated with fusing all data by Bayesian method.The assessment of the reliability and the degradation process of the cutting tool can be obtained.At the same time,this work proposes a reliability assessment model to consider the diversity of degradation process of the cutting tool in same condition.The change trend of the cutting tool with time is also obtained according to the reliability assessment of the cutting tool.(3)In order to illustrate the above two mentioned methods,a case on milling difficult-to-machine materials(TC4)is studied.The degradation data is from an orthogonal experiment with three factors and three levels The number of measurement of tool wear is 10,which means that the cutting processing is interrupted by 10 times and the time of each processing depends on the feed rate.The above methods are illustrated based on the degradation data.Besides the wear amount of the cutting tool,the relevant data are also collected: vibrations signals on spindle and worktable,surface roughness of workpiece and chip data(width of chip and radian of chip).The wear state of the cutting tool can be monitored from multi-angle with the above relevant data.A comprehensive database of the cutting tool is set up in this work.The calculation results of the wear amount of the cutting tool demonstrate that the proposed methods in this thesis are suited for reliability assessment of the cutting tool,which provides a theoretical support for the process planning of numerical control machine and intelligence choice of machine tool.