PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 15, 2026IEEE Transactions on Visualization and Computer Graphics0 citations

Outer Contour-Driven Ruled Surface Generation for Linear Hot-Wire Rough Machining

View Full Paper
ZZZ ZhangKWKang WuYLY. Li

Key Points

  • The aim is to create ruled surfaces that effectively remove material without collisions during hot-wire machining.
  • Developed an iterative algorithm for ruled surface generation.
  • Used a genetic algorithm for viewpoint optimization to enhance material removal.
  • Implemented an adaptive fitting algorithm for producing constrained smooth curves.
  • Demonstrated feasibility through 10 physical examples.
  • Achieved lower errors in cut precision compared to manual designs.
  • Maintained the same number of cuts while ensuring collision-free machining.

Abstract

We propose a novel method to generate a small set of ruled surfaces that do not collide with the input shape for linear hot-wire rough machining. Central to our technique is a new observation: ruled surfaces constructed by vertical extrusion from planar smooth curves that approach the input shape's outer contour lines without collisions can effectively remove material during rough machining. Accordingly, we develop an iterative algorithm that alternates in each iteration between computing a viewpoint to determine an outer contour line and optimizing a smooth curve to approximate that contour line under the collision-free constraint. Specifically, a view selection approach based on a genetic algorithm is used to optimize the viewpoint for removing materials as much as possible, and an adaptive fitting algorithm is presented to find the constrained curves. The feasibility and practicability of our method are demonstrated through 10 physical examples. Compared with manual designs, our method obtains lower errors with the same number of cuts.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69b64ccdb42794e3e660e014https://doi.org/10.1109/tvcg.2026.3672469
Ask AI
Helpful
Bookmark
Share
View Full Paper