Journal of Pure and Applied MicrobiologyVol. 7 No. Special Edition

Degradation Information-Based Instantaneous Reliability Prediction of Cutting Tool

Baojia Chen1*, Li Li1, Xuefeng Chen2, Zhengjia He2, Gaigai Cai2 and Wenrong Xiao2

1Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance, China Three Gorges University, Yichang, China. 2State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, China.

Received on 03 March 2013 and accepted on 14 April 2013



In order to predict the reliability of cutting tools, whose failure is mainly caused by degradation, a forecasting method based on degradation information is proposed, which includes: extraction of degradation indices?computation of instantaneous reliability?establishment and application of the neural network prediction model. The key issue of prediction accuracy is the computation of instantaneous reliability. A novel approach incorporated Bayes theorem and Kaplan-Meier (KM) estimator principle is employed to calculate the instantaneous reliability. As validated by the time-varying wear data of the tools?the trained network is available of predicting the failure time accurately judging by the criterion of reliability. The results show the feasibility and effectiveness to predict reliability based on degradation information.

Keywords : Degradation Information, Cutting Tool, Reliability Prediction, Instantaneous Reliability.