The integration of Reverse Engineering (RE) and Additive Manufacturing (AM) is transforming modern product development, enabling capabilities in customization, repair, and digital manufacturing. In parallel, Artificial Intelligence (AI) techniques, ranging from machine learning to deep learning, are revolutionizing both data acquisition and decision-making processes across the digital thread.

This Special Issue aims to explore the emerging paradigm of AI-driven RE-to-AM workflows, where intelligent algorithms enhance the acquisition, reconstruction, optimization, and fabrication of components across different technical and scientific domains. The focus is, in particular, on methodological advances, enabling technologies, and cross-domain applications, including industrial manufacturing, biomedical engineering, cultural heritage, and fashion/textile sectors.

The Special Issue seeks to bridge the gap between data-based reconstruction and modeling, intelligent process planning, and advanced additive manufacturing strategies. Topics of interest include, but are not limited to:
• AI-based 3D reconstruction and geometric modeling
• Machine learning for point cloud processing and mesh optimization
• Intelligent scan-to-CAD and scan-to-print workflows
• Design for Additive Manufacturing (DFAM)
• AI-assisted topology optimization and generative design
• Defect detection and quality control using computer vision
• In-situ monitoring and predictive modeling in AM processes
• Integration of GD&T and metrology in AI-driven AM pipelines
• Digital twins for RE and AM integration
• Multi-material and functionally graded AM enabled by AI
• AI-based or AI-enhanced 3D printing parameter optimization
• Applications in:
o Biomedical and patient-specific devices
o Cultural heritage and digital restoration
o Textile and fashion engineering
o Industrial inspection and remanufacturing