Adaptive Toolpath Generation

Adaptive Toolpath Generation is a toolpath generation methodology that dynamically adjusts cutting parameters and path geometry in real time based on sensor feedback or process conditions to optimize machining performance, distinguishing itself from conventional methods by its responsiveness to in-process variations.

44

Publications

1.5K

Citations

126

Authors

59

Institutions

Publications per year

2017–2026

13

Authors

126

  1. SD
    Songlin Ding

    RMIT University, Australia

    2 publications · 213 citations

    2

    h-index

  2. SQ
    Shuo Qu

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 42 citations

    2

    h-index

  3. KT
    Kai Tang

    Hong Kong University of Science and Technology, Hong Kong SAR China

    2 publications · 59 citations

    2

    h-index

  4. JD
    Junhao Ding

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 42 citations

    2

    h-index

  5. DC
    Daniel C. H. Yang

    University of California, Los Angeles, United States

    2 publications · 213 citations

    2

    h-index

1–5 of 126

Venues

  1. 10

    h-index

  2. International Journal of Production Research

    4 publications · 155 citations

    4

    h-index

  3. Computer-Aided Design

    3 publications · 208 citations

    3

    h-index

  4. Journal of Manufacturing Systems

    2 publications · 45 citations

    2

    h-index

  5. Journal of Manufacturing Processes

    JMP · 2 publications · 51 citations

    2

    h-index

1–5