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Related Experiment Video

Updated: Jan 13, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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A Machine Vision-Enhanced Framework for Tracking Inclusion Evolution and Enabling Intelligent Cleanliness Control in

Yong Lyu1,2, Yunhai Jia2, Lixia Yang2

  • 1School of Metallurgical and Ecological Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Materials (Basel, Switzerland)
|January 10, 2026
PubMed
Summary
This summary is machine-generated.

A new system accurately analyzes non-metallic inclusions in High-Strength Low-Alloy (HSLA) steel across production stages. It reveals how electroslag remelting and forging refine inclusions, enabling better quality control.

Keywords:
High-Strength Low-Alloy (HSLA) steelcleanliness controlfull-range analysis systeminclusion evolutionintelligent inspectionnon-metallic inclusions

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Area of Science:

  • Metallurgical Engineering
  • Materials Science
  • Analytical Chemistry

Background:

  • Non-metallic inclusions in High-Strength Low-Alloy (HSLA) steel significantly impact performance.
  • Conventional methods struggle with accurate inclusion characterization in large components.
  • Understanding inclusion behavior throughout processing is crucial for quality control.

Purpose of the Study:

  • To develop an integrated system for automated, full-process analysis of non-metallic inclusions in HSLA steel.
  • To investigate the evolution and distribution of inclusions from electrode to forged billet.
  • To provide insights for optimizing HSLA steel production processes.

Main Methods:

  • Development of an integrated analysis system combining motion control, optical imaging, and laser spectral analysis.
  • Systematic sampling and analysis across the industrial process chain: consumable electrode, electroslag remelting (ESR) ingot, and forged billet.
  • Utilizing an intelligent analysis framework with a YOLOv11 detection model and spectral feedback.

Main Results:

  • Electroslag remelting (ESR) effectively reduced Type D inclusions.
  • Type C silicate inclusions showed significant enrichment in the ESR ingot tail due to solidification dynamics.
  • Subsequent forging led to substantial refinement and dispersion, achieving high purity in the billet tail.

Conclusions:

  • The developed system enables rapid, automated, and compositional analysis of inclusions in meter-scale HSLA steel samples.
  • Key process insights were gained, highlighting the roles of ESR and forging in inclusion control.
  • Enhanced process strategies and an intelligent analysis framework were proposed for achieving controllable defect levels in HSLA steel.