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AI and Quantum Computing Enhance Additive Manufacturing Monitoring

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore the application of AI and quantum computing in additive manufacturing. The first paper details a hybrid approach using machine learning, specifically a combination of EfficientNetB0 and Random Forest, for real-time monitoring of melt pools in laser powder bed fusion (LPBF). This method achieved high accuracy and efficiency, outperforming purely deep learning models. The second paper presents a hybrid quantum-classical model that utilizes quantum computing for feature extraction in melt pool prediction for LPBF, demonstrating potential improvements over classical methods by leveraging quantum entanglement and superposition. AI

IMPACT These hybrid approaches demonstrate potential for improved efficiency and accuracy in manufacturing processes, paving the way for more robust quality control.

RANK_REASON Two academic papers published on arXiv detailing novel applications of AI and quantum computing in manufacturing.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

AI and Quantum Computing Enhance Additive Manufacturing Monitoring

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Two academic papers published on arXiv detailing novel applications of AI and quantum computing in manufacturing.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Inioluwa Emmanuel, Zhuo Yang, Ho Yeung, Xinyao Zhang ·

    Machine Learning Modeling for Real-Time Melt Pool Monitoring in Laser Powder Bed Fusion Additive Manufacturing: A Hybrid Approach

    arXiv:2606.23851v1 Announce Type: new Abstract: This work investigates the implementation of artificial intelligence and machine learning (AI/ML) for real-time monitoring in laser powder bed fusion (LPBF) additive manufacturing. We developed a binary image classification framewor…

  2. arXiv cs.LG TIER_1 English(EN) · Matthew M. Sato, Kincho H. Law ·

    A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion

    arXiv:2606.23719v1 Announce Type: cross Abstract: Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools from process parameters is crucial for assessing quality prior to manufacturing but…

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