4.5 Review

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

Publisher

KOREAN SOC PRECISION ENG
DOI: 10.1007/s40684-018-0057-y

Keywords

4th industrial revolution; Artificial intelligence; Machine learning; Machining process; Machining industry

Funding

  1. Basic Research Lab Program through the National Research Foundation of Korea (NRF) - MSIT [2018R1A4A1059976]
  2. SNU-Hojeon Garment Smart Factory Research Center - Hojeon Ltd.
  3. Korea Basic Science Institute (KBSI) Creative Convergence Research Project - National Research Council of Science and Technology (NST) in Korea [CAP-PN2017003]
  4. Creative-Pioneering Researchers Program through Seoul National University
  5. Future Research Committee - Seoul National University in Korea
  6. National Research Council of Science & Technology (NST), Republic of Korea [1711062055] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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.

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