Fuzzy reliability estimation for cutting tools

Shujie Liu, Hongchao Zhang, Chao Li, Huitian Lu, Ya Wei Hu

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

A cutting tool is an important part of machine tools and its reliability influences the total manufacturing effectiveness and stability of machine tools. The paper presents the application of state space model in the cutting tool reliability assessment. As the single evaluation threshold is not easy to determine, the paper puts forward the concept of fuzzy threshold to solve this problem. We use the performance or substitute variable to fuzzify the states of the system and the success/failure events are treated as fuzzy sets. The acoustic emission signal is measured in the test, and wavelet packet (WP) energy extracted from the acoustic emission signal is used to estimate the tool state. The deterioration of the system is seen as a stochastic dynamic process with continuous degrading. The deterioration tendency is predicted by the Kalman filter algorithm, and the corresponding fuzzy reliability is calculated based on the forecasted deterioration state and a pre-set fuzzy threshold. The best time of when the tool should be replaced can be obtained from the decision making model.

Original languageEnglish
Pages (from-to)62-67
Number of pages6
JournalProcedia CIRP
Volume15
DOIs
StatePublished - 2014

Keywords

  • Cutting tool
  • Fuzzy reliability
  • Kalman filter
  • State space model

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