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Operation of the Collaborative Composite Manufacturing CCM System

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An Agent-Based Method for Feature Recognition and Path Optimization of Computer Numerical Control Machining

Purui Li^1,2, Meng Chen^1,2, Chuanhao Ji^1,2

¹Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang 110168, China.

Sensors (Basel, Switzerland)

|September 14, 2024

Summary

This summary is machine-generated.

This study introduces an intelligent agent-based method for optimizing CNC machining paths. The approach uses deep learning for feature recognition and advanced algorithms to smooth tool paths, reducing defects in intelligent manufacturing.

Keywords:

CNC system deep learning feature recognition intelligent elements path optimization process analysis

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Area of Science:

Manufacturing Engineering
Artificial Intelligence
Computer-Aided Manufacturing

Background:

Traditional CNC machining often produces defects due to G01 collinear motion commands causing path curvature discontinuities.
Intelligent manufacturing increasingly utilizes AI, especially deep learning, for feature recognition in geometric shapes.

Purpose of the Study:

To propose a novel method for CNC machining trajectory feature recognition and path optimization using intelligent agents.
To address and mitigate machining defects caused by discontinuous tool paths.

Main Methods:

Intelligent agents are employed for G-code analysis and geometric information extraction.
The MCRL deep learning model with linear attention and multiple neural networks is used for recognition and classification.
Path optimization is achieved via mean filtering, Bézier curve fitting, and a novel adaptive coati optimization algorithm (NACOA).

Main Results:

The proposed method significantly enhances the smoothness of CNC machining paths.
Machining defects are substantially reduced through optimized tool trajectories.
Validation was performed on gear, pentagram boss, and maple leaf models.

Conclusions:

The intelligent agent-based approach offers a viable solution for improving CNC machining quality.
This method demonstrates substantial application value in intelligent manufacturing by enhancing path smoothness and reducing defects.