Automated Determination of Indexing Orientations and Tool Path Generation for 5-Axis Machining of Complex Shapes

Kentaro Matsukawa et al.

International Journal of Automation Technology2026https://doi.org/10.20965/ijat.2026.p0078article
ABDC C
Weight
0.37

What the paper says

In response to the increasing demand for high-mix, low-volume production and the simultaneous shortage of experienced workers, the use of 5-axis controlled machine tools has attracted growing attention. Although complex solid shapes that include free-form surfaces are typically machined using simultaneous 5-axis machining, generation of corresponding numerical control programs continues to depend heavily on the expertise and judgment of experienced operators, rendering parts of the process highly reliant on individual proficiency. In contrast, 5-axis indexing machining involves fewer degrees of freedom compared to simultaneous 5-axis machining. Therefore, by fixing the tool orientation, it achieves easier control and higher machining stability, rendering it suitable for automation. This study developed an automated system that determines both the indexing orientations and tool paths for 5-axis indexing machining, using standard triangulated language format computer-aided design models of complex shapes as input. The system includes a shape removal simulation based on the dexel model, which automatically identifies air-cut regions for each indexing orientation and subsequently generates efficient, waste-free tool paths. Additionally, by leveraging parallel processing on a graphics processing unit, the system accelerates critical operations including tool orientation determination, tool path generation, and air-cut detection, thereby achieving practical computation times for automated process planning.

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https://doi.org/https://doi.org/10.20965/ijat.2026.p0078

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@article{kentaro2026,
  title        = {{Automated Determination of Indexing Orientations and Tool Path Generation for 5-Axis Machining of Complex Shapes}},
  author       = {Kentaro Matsukawa et al.},
  journal      = {International Journal of Automation Technology},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.20965/ijat.2026.p0078},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.