TY - JOUR
T1 - Smart Machining Process Using Machine Learning
T2 - A Review and Perspective on Machining Industry
AU - Kim, Dong Hyeon
AU - Kim, Thomas J.Y.
AU - Wang, Xinlin
AU - Kim, Mincheol
AU - Quan, Ying-Jun
AU - Oh, Jin Woo
AU - Min, Soo-Hong
AU - Kim, Hyungjung
AU - Bhandari, Binayak
AU - Yang, Insoon
AU - Ahn, Sung-Hoon
N1 - Publisher Copyright:
© 2018, Korean Society for Precision Engineering.
PY - 2018/8/1
Y1 - 2018/8/1
N2 - 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.
AB - 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.
KW - 4th industrial revolution
KW - Artificial intelligence
KW - Machine learning
KW - Machining industry
KW - Machining process
KW - n/a OA procedure
UR - http://www.scopus.com/inward/record.url?scp=85052233025&partnerID=8YFLogxK
U2 - 10.1007/s40684-018-0057-y
DO - 10.1007/s40684-018-0057-y
M3 - Review article
SN - 2288-6206
VL - 5
SP - 555
EP - 568
JO - International Journal of Precision Engineering and Manufacturing - Green Technology
JF - International Journal of Precision Engineering and Manufacturing - Green Technology
IS - 4
ER -