TY - JOUR
T1 - The state-of-art review of ultra-precision machining using text mining: Identification of main themes and recommendations for the future direction
AU - Yip, Wai Sze
AU - Yan, Hengzhou Edward
AU - Zhang, Baolong
AU - To, Suet
N1 - Funding Information:
The work described in this article was supported by the funding support to the State Key Laboratories in Hong Kong from the Innovation and Technology Commission (ITC) of the Government of the Hong Kong Special Administrative Region (HKSAR) (project code: BBR3), China and the Research Office (project code: BBXM and BBX) of The Hong Kong Polytechnic University. The Project of Strategic Importance of the Hong Kong Polytechnic University (project code: ZE0G and SBBD).
Publisher Copyright:
© 2023 Wiley Periodicals LLC.
PY - 2024/1
Y1 - 2024/1
N2 - Ultra-precision machining (UPM), one of the most advanced machining techniques that can produce exact components, significantly impacts the technological community. The significance of UPM attracts the attention of academic and industrial partners. As a result of the rapid development of UPM caused by technological advancement, it is necessary to revisit the current stages and evolution of UPM to sustain and advance this technology. The state of the art in UPM is first investigated systematically in this study by identifying the current four major UPM themes. The UPM thematic network is then built, along with a structural analysis of the network, to determine the interactions between each theme and the primary roles of theme members responsible for the interactions. Furthermore, the “bridge” role is assigned to the specific UPM theme content. On the other hand, Sentiment analysis is conducted to determine how the academic community at UPM feels about the themes for UPM research to focus on those themes with a need for more confidence. Considering the above findings, the future perspective of UPM and suggestions for its advancement are discussed and provided. This study provides a comprehensive understanding and the current state-of-the-art review of UPM technology by a text mining technique to critically analyze its research content, as well as suggestions to enhance UPM development by focusing on its current challenges, thereby assisting academia and institutions in leveraging this technology to benefit society. This article is categorized under: Algorithmic Development > Text Mining Application Areas > Science and Technology Application Areas > Industry Specific Applications.
AB - Ultra-precision machining (UPM), one of the most advanced machining techniques that can produce exact components, significantly impacts the technological community. The significance of UPM attracts the attention of academic and industrial partners. As a result of the rapid development of UPM caused by technological advancement, it is necessary to revisit the current stages and evolution of UPM to sustain and advance this technology. The state of the art in UPM is first investigated systematically in this study by identifying the current four major UPM themes. The UPM thematic network is then built, along with a structural analysis of the network, to determine the interactions between each theme and the primary roles of theme members responsible for the interactions. Furthermore, the “bridge” role is assigned to the specific UPM theme content. On the other hand, Sentiment analysis is conducted to determine how the academic community at UPM feels about the themes for UPM research to focus on those themes with a need for more confidence. Considering the above findings, the future perspective of UPM and suggestions for its advancement are discussed and provided. This study provides a comprehensive understanding and the current state-of-the-art review of UPM technology by a text mining technique to critically analyze its research content, as well as suggestions to enhance UPM development by focusing on its current challenges, thereby assisting academia and institutions in leveraging this technology to benefit society. This article is categorized under: Algorithmic Development > Text Mining Application Areas > Science and Technology Application Areas > Industry Specific Applications.
KW - sentiment analysis
KW - technological evolution
KW - text mining
KW - the state-of-the-art
KW - thematic network analysis
KW - ultra-precision machining
UR - http://www.scopus.com/inward/record.url?scp=85174170933&partnerID=8YFLogxK
U2 - 10.1002/widm.1517
DO - 10.1002/widm.1517
M3 - Journal article
AN - SCOPUS:85174170933
SN - 1942-4787
VL - 14
JO - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
JF - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
IS - 1
M1 - e1517
ER -