Integrated optimisation of surface roughness and tool performance when face milling 416 SS

Patricia Muñoz-Escalona*, Paul Maropoulos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

Tool life is an important factor to be considered during the optimisation of a machining process since cutting parameters can be adjusted to optimise tool changing, reducing cost and time of production. Also the performance of a tool is directly linked to the generated surface roughness and this is important in cases where there are strict surface quality requirements. The prediction of tool life and the resulting surface roughness in milling operations has attracted considerable research efforts. The research reported herein is focused on defining the influence of milling cutting parameters such as cutting speed, feed rate and axial depth of cut, on three major tool performance parameters namely, tool life, material removal and surface roughness. The research is seeking to define methods that will allow the selection of optimal parameters for best tool performance when face milling 416 stainless steel bars. For this study the Taguchi method was applied in a special design of an orthogonal array that allows studying the entire parameter space with only a number of experiments representing savings in cost and time of experiments. The findings were that the cutting speed has the most influence on tool life and surface roughness and very limited influence on material removal. By last tool life can be judged either from tool life or volume of material removal.

Original languageEnglish
Pages (from-to)248-256
Number of pages9
JournalInternational Journal of Computer Integrated Manufacturing
Volume23
Issue number3
DOIs
Publication statusPublished - 19 Feb 2010
Externally publishedYes

Keywords

  • Material removal
  • Milling
  • Surface roughness
  • Tool life
  • Tool wear

ASJC Scopus subject areas

  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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