Productivity Progression with Tool Wear in Titanium Milling

Joyson Menezes, Mark A. Rubeo, Kadir Kiran, Andrew Honeycutt, Tony L. Schmitz

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This paper presents experimental results for flank wear width, cutting force, temperature, and surface finish with increasing tool wear in titanium (Ti6Al4V) milling. The variation in these process indicators is presented for repeated trials as the wear progresses from a new tool condition to a significantly worn state. Based on the measured force data, cutting force coefficients are determined using a nonlinear optimization algorithm as the tool wears and these coefficients are combined with the structural dynamics to predict the process stability. The achievable chatter-free material removal rate is then computed for both the new and worn tool conditions. In this way, the variation in productivity is related to the wear state. As expected, the productivity reduces with increase wear.

Original languageEnglish (US)
Pages (from-to)427-441
Number of pages15
JournalProcedia Manufacturing
Volume5
DOIs
StatePublished - 2016

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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