Smart Machining Process Using Machine Learning: A Review and Perspective on Machining Industry

Dong Hyeon Kim, Thomas J.Y. Kim, Xinlin Wang, Mincheol Kim, Ying-Jun Quan, Jin Woo Oh, Soo-Hong Min, Hyungjung Kim, Binayak Bhandari, Insoon Yang, Sung-Hoon Ahn*

*Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

258 Citations (Scopus)

Abstract

The Fourth Industrial Revolution incorporates the digital revolution into the physical world, creating a new direction in a number of fields, including artificial intelligence, quantum computing, nanotechnology, biotechnology, robotics, 3D printing, autonomous vehicles, and the Internet of Things. The artificial intelligence field has encountered a turning point mainly due to advancements in machine learning, which allows machines to learn, improve, and perform a specific task through data without being explicitly programmed. Machine learning can be utilized with machining processes to improve product quality levels and productivity rates, to monitor the health of systems, and to optimize design and process parameters. This is known as smart machining, referring to a new machining paradigm in which machine tools are fully connected through a cyber-physical system. This paper reviews and summarizes machining processes using machine learning algorithms and suggests a perspective on the machining industry.

Original languageEnglish
Pages (from-to)555-568
Number of pages14
JournalInternational Journal of Precision Engineering and Manufacturing - Green Technology
Volume5
Issue number4
DOIs
Publication statusPublished - 1 Aug 2018
Externally publishedYes

Keywords

  • 4th industrial revolution
  • Artificial intelligence
  • Machine learning
  • Machining industry
  • Machining process
  • n/a OA procedure

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