Dynamic reliability analysis of cutting tool for milling difficult to machine materials Ti-6Al-4V

• Published in: 2016 Prognostics and System Health Management Conference (PHM-Chengdu) pp. 1 - 6
• Main Authors: Yan Guo, Peipei Zhang, Bo Wang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2016
• Subjects: Cutting tools; difficult-to-machine materials; Machining; Materials reliability; reliability; Software; Software reliability; SPSS software; Titanium alloys; wear amount of the cutting tool
• ISSN: 2166-5656
• DOI: 10.1109/PHM.2016.7819915

Difficult-to-machine materials is widely used in aerospace. Titanium alloy (Ti-6Al-4V) by using computer numerical control (CNC) machining is studied in order to improve the processing efficiency of Ti-6Al-4V. The wear amount of cutting tool as a key part of CNC is one of the most important representation for the machining efficiency and the stability for cutting difficult-to machine materials. An estimating method for difficult-to-machine materials is proposed to assess dynamic reliability of tool wear based on the gradual wear process in order to identify directly and accurately the stage of tool wear and improve machining efficiency. Firstly, the wear amount of cutting tool which is measured on the experiment is analyzed statistically through using SPSS software to determine the distributions of the wear amount of cutting tool. The results display that the wear amount of cutting tool in each group is subject to lognormal distribution. Secondly, the lognormal distribution is verified whether it is reasonable to conform to the wear amount of cutting tool with SPSS software in K-S inspection. Then, the linear regression equation method is proposed to estimate the parameters of lognormal distribution. After that, the discrete dynamic reliability assessment model of tool wear is derived from traditional assessment model of tool life. Finally, the tool wear performance is used to judge the correctness of the model. The results show that the tendency of tool wear reliability coincides with the state of tool wear over time. This method can also be extended to other gradual failure.