Adaptive Process Planning

Adaptive Process Planning is a manufacturing process planning approach that dynamically modifies process parameters and sequences in response to real-time production disturbances and system feedback, distinguishing itself from static or predefined planning methods by its capacity for on-the-fly adjustment and continuous optimization.

32

Publications

1.8K

Citations

87

Authors

48

Institutions

Publications per year

2017–2026

6

Authors

87

  1. LW
    Lihui Wang

    KTH Royal Institute of Technology, Sweden

    6 publications · 314 citations

    6

    h-index

  2. TR
    Tyson R. Browning

    Texas Christian University, United States

    2 publications · 159 citations

    2

    h-index

  3. EZ
    Eyal Zussman

    Technion – Israel Institute of Technology, Israel

    2 publications · 126 citations

    2

    h-index

  4. MM
    Massimo Mecella

    Sapienza University of Rome, Italy

    2 publications · 47 citations

    2

    h-index

  5. VL
    Viktor Lévárdy

    Texas Christian University, United States

    2 publications · 159 citations

    2

    h-index

1–5 of 87

Venues

  1. Robotics and Computer-Integrated Manufacturing

    3 publications · 260 citations

    3

    h-index

  2. CIRP Annals

    2 publications · 96 citations

    2

    h-index

  3. Journal of Manufacturing Systems

    3 publications · 176 citations

    2

    h-index

  4. International Journal of Production Research

    3 publications · 82 citations

    2

    h-index

  5. Research in Engineering Design

    2 publications · 66 citations

    2

    h-index

1–5