TY - JOUR
T1 - A review: Insight into smart and sustainable ultra-precision machining augmented by intelligent IoT
AU - Xu, Zhicheng
AU - Zhu, Tong
AU - Luo, Fan Louis
AU - Zhang, Baolong
AU - Poon, Hiuying
AU - Yip, Wai Sze
AU - To, Suet
N1 - Funding Information:
The work described in this paper was fully supported by the funding for Projects of Strategic Importance of The Hong Kong Polytechnic University (Project Code: 1-ZE0G).
Publisher Copyright:
© 2024 The Society of Manufacturing Engineers
PY - 2024/6
Y1 - 2024/6
N2 - Ultra-precision machining (UPM), which is capable of fabricating micro-components with less than 0.2 µm forming accuracy and 10 nm surface accuracy, is becoming increasingly important due to its indispensable and widespread application in various high-tech fields such as optics, electrics, and semiconductor. However, the low energy and machining efficiency of UPM is getting more prominent. Current efforts have primarily focused on either the smart or sustainability aspect, with limited integration between the two. Thus, there remains a gap in achieving comprehensive and cohesive solutions that meet both objectives. With the advent of the Internet of Things (IoT), current UPM has the opportunity to leverage technology and knowledge to achieve sustainability through a smart machining system. Herein, this work firstly revealed and summarized the state of current UPM, including engineering issues, intrinsic correlation, and technique challenges of both smart UPM and sustainable UPM. Importantly, the feasible solutions combining these emerging technologies for these technique challenges were presented for the first time. Finally, an intelligent six-layers IoT framework was presented to realize optimal monitoring, high-speed data collection and transmission, real-time machining error compensation, multi-objectives optimization, intelligent failure detection, and machine-human interaction, ultimately implementing smart and sustainable UPM. This work provides significant insight into future technological innovation at UPM for relevant industries and academia.
AB - Ultra-precision machining (UPM), which is capable of fabricating micro-components with less than 0.2 µm forming accuracy and 10 nm surface accuracy, is becoming increasingly important due to its indispensable and widespread application in various high-tech fields such as optics, electrics, and semiconductor. However, the low energy and machining efficiency of UPM is getting more prominent. Current efforts have primarily focused on either the smart or sustainability aspect, with limited integration between the two. Thus, there remains a gap in achieving comprehensive and cohesive solutions that meet both objectives. With the advent of the Internet of Things (IoT), current UPM has the opportunity to leverage technology and knowledge to achieve sustainability through a smart machining system. Herein, this work firstly revealed and summarized the state of current UPM, including engineering issues, intrinsic correlation, and technique challenges of both smart UPM and sustainable UPM. Importantly, the feasible solutions combining these emerging technologies for these technique challenges were presented for the first time. Finally, an intelligent six-layers IoT framework was presented to realize optimal monitoring, high-speed data collection and transmission, real-time machining error compensation, multi-objectives optimization, intelligent failure detection, and machine-human interaction, ultimately implementing smart and sustainable UPM. This work provides significant insight into future technological innovation at UPM for relevant industries and academia.
KW - In-process monitoring and algorithms
KW - Internet of things
KW - Smart ultra-precision machining
KW - Sustainable ultra-precision machining
KW - Ultra-precision machining
UR - http://www.scopus.com/inward/record.url?scp=85188558722&partnerID=8YFLogxK
U2 - 10.1016/j.jmsy.2024.03.008
DO - 10.1016/j.jmsy.2024.03.008
M3 - Review article
AN - SCOPUS:85188558722
SN - 0278-6125
VL - 74
SP - 233
EP - 251
JO - Journal of Manufacturing Systems
JF - Journal of Manufacturing Systems
ER -