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Background <p>Joining dissimilar metals such as Inconel 625 and 316Lstainless steel is difficult due to porosity, low toughness, and poor corrosion resistance in the weld zone. Improving weld quality requires innovative techniques and optimized process parameters.</p> Aim <p>This study aims to enhance weld quality by applying Ultrasonic Vibration-Assisted Laser Beam Welding (USALW) and to optimize key parameters influencing mechanical and corrosion performance.</p> Methods <p>A Response Surface Methodology–Box Behnken Design(RSM-BBD) was used to evaluate the effects of laser power, ultrasonic power, weld bead clearance (WBC), and shielding gas flow rate. Mechanical tests, corrosion analysis, and SEM microstructural examination were performed. An Interpretable Artificial Intelligence (IAI) model combining RNN, LIME, and MFO was developed for prediction and explanation of weld responses.</p> Results <p>Optimal parameters such as laser power 2000 W, ultrasonic power 500 W,WBC 1.73 mm, and shielding gas flow 20 L/min yielded a weld penetration of 2.99 mm, tensile strength of 1099.98 MPa, impact toughness of 79.65 J, and corrosion resistance of 0.99 mm/yr. WBC emerged as the most influential factor, significantly affecting penetration, strength, and toughness. Higher laser power and WBC improved corrosion resistance. SEM analysis confirmed grain refinement and enhanced fusion due to ultrasonic vibration.</p> Conclusion <p>USALW significantly improves weld quality in dissimilar joints of Inconel 625 and 316L steel. The proposed IAI framework provides accurate predictions and transparent interpretation of parameter effects, supporting robust optimization and practical engineering decisions.</p>

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Enhanced Weld Quality and Interpretability in Ultrasonic-Assisted Laser Welding of Dissimilar Metals Using a Hybrid AI Framework

  • 期刊论文

  • 发表日期：

    2025年12月5日

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  • B. Veera Jyothi,
  • L. Suresh Kumar,
  • P. V. R. Ravindra Reddy,
  • K. Amudha,
  • S. Balu

摘要

Background

Joining dissimilar metals such as Inconel 625 and 316Lstainless steel is difficult due to porosity, low toughness, and poor corrosion resistance in the weld zone. Improving weld quality requires innovative techniques and optimized process parameters.

Aim

This study aims to enhance weld quality by applying Ultrasonic Vibration-Assisted Laser Beam Welding (USALW) and to optimize key parameters influencing mechanical and corrosion performance.

Methods

A Response Surface Methodology–Box Behnken Design(RSM-BBD) was used to evaluate the effects of laser power, ultrasonic power, weld bead clearance (WBC), and shielding gas flow rate. Mechanical tests, corrosion analysis, and SEM microstructural examination were performed. An Interpretable Artificial Intelligence (IAI) model combining RNN, LIME, and MFO was developed for prediction and explanation of weld responses.

Results

Optimal parameters such as laser power 2000 W, ultrasonic power 500 W,WBC 1.73 mm, and shielding gas flow 20 L/min yielded a weld penetration of 2.99 mm, tensile strength of 1099.98 MPa, impact toughness of 79.65 J, and corrosion resistance of 0.99 mm/yr. WBC emerged as the most influential factor, significantly affecting penetration, strength, and toughness. Higher laser power and WBC improved corrosion resistance. SEM analysis confirmed grain refinement and enhanced fusion due to ultrasonic vibration.

Conclusion

USALW significantly improves weld quality in dissimilar joints of Inconel 625 and 316L steel. The proposed IAI framework provides accurate predictions and transparent interpretation of parameter effects, supporting robust optimization and practical engineering decisions.