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

2 Scopus citations

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 triaxial 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)597-603
Number of pages7
JournalAmerican Society of Mechanical Engineers, Manufacturing Engineering Division, MED
Volume10
Publication statusPublished - 1999

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

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