Development of a cutting direction and sensor orientation independent monitoring technique for end-milling

John Timothy Roth, Sudhakar M. Pandit

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In the authors’ previous work, univariate models were fit to acceleration data to predict impending tool failure. Numerous end-milling life tests, conducted under a wide variety of cutting conditions, demonstrated that the method could consistently warn of impending failure between 6 inches (15 cm) and 8 inches (20 cm) prior to the actual event. This paper presents an improved method that increases the warning time and allows the technique to function independent of the cutting direction or sensor orientation. Using multivariate autoregressive models fit to tri-axial accelerometer signals, monitoring indices are developed, verified and the results are compared with those from the univariate models. The multivariate models detected impending failure 30 inches (76 cm) prior to its occurrence, 23.5 inches (60 cm) earlier than with the univariate models. Furthermore, the multivariate models are able to monitor the condition of the tool, regardless of the cutting direction or sensor orientation.

Original languageEnglish (US)
Pages (from-to)671-677
Number of pages7
JournalJournal of Manufacturing Science and Engineering, Transactions of the ASME
Volume122
Issue number4
DOIs
StatePublished - Jan 1 2000

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Monitoring
Sensors
Accelerometers

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

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