Tool life prediction using Bayesian updating

Jaydeep M. Karandikar, Tony L. Schmitz, Ali E. Abbas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

According to the Taylor tool life equation, tool life reduces with cutting speed according to a power law. The relationship is quantified using an exponent, n, and a constant, C, which are tool-workpiece dependent. However, tool wear is also considered to be a stochastic process and difficult to predict. The Taylor tool life model is deterministic and there is inherent uncertainty in the empirical constants, n and C. In this work, Bayesian inference is applied to estimate the Taylor tool life constants using a discrete grid method. Tool wear tests are performed using an uncoated carbide tool and 1018 steel workpiece. The test results are used to update the beliefs about the Taylor tool life constants. The updated beliefs are then used to predict tool life using a probability distribution function.

Original languageEnglish
Title of host publication39th North American Manufacturing Research Conference 2011 - Transactions of the North American Manufacturing Research Institution of SME
Pages466-475
Number of pages10
StatePublished - 2011
Externally publishedYes
Event39th Annual North American Manufacturing Research Conference, NAMRC39 - Corvallis, OR, United States
Duration: Jun 13 2011Jun 17 2011

Publication series

NameTransactions of the North American Manufacturing Research Institution of SME
Volume39
ISSN (Print)1047-3025

Conference

Conference39th Annual North American Manufacturing Research Conference, NAMRC39
Country/TerritoryUnited States
CityCorvallis, OR
Period06/13/1106/17/11

Keywords

  • Bayesian updating
  • Discrete grid method
  • Taylor tool life
  • Tool wear

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