The state‐of‐art review of ultra‐precision machining using text mining: Identification of main themes and recommendations for the future direction

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.

• Publication year

  2023

• Venue

  WIREs Data. Mining. Knowl. Discov.

• Publication date

  2023-10-15

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1002/widm.1517
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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