Revisiting machinability assessment: Towards total machining performance

I. S. Jawahir, Helmi Attia, Martin Dix, Hassan Ghadbeigi, Zhirong Liao, Julius Schoop, Alborz Shokrani

Research output: Contribution to journalArticlepeer-review

Abstract

The term “machinability”, introduced over hundred years ago, is vague and cannot fully describe the performance of machining systems. Machinability databases established over many decades are outdated: missing recent advances, e.g., cutting tool grades, geometry, coatings, and cutting fluids effects. This keynote paper summarizes findings of a CIRP-sponsored three-year collaborative study in five interrelated topics. The paper presents a critical review of the state-of-the-art on these topics, the results of two major round robin tests, three industry-based case studies, and a novel predictive system of machining performance, utilizing advanced deep learning methods. Outlook and future directions are also presented.

Original languageEnglish
JournalCIRP Annals
DOIs
StateAccepted/In press - 2025

Bibliographical note

Publisher Copyright:
© 2025 CIRP

Keywords

  • Cutting tool
  • Machinability
  • Modeling

ASJC Scopus subject areas

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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