Dear Colleagues,

The adoption of intelligent and sustainable solutions in medical additive manufacturing is changing the manufacturing process of healthcare and clinical engineering. This theme emphasizes the importance of artificial intelligence, machine learning and data-driven analytics in streamlining process control, providing product reliability and facilitating real-time decision-making in clinical environments. Robotics and automation are laying the groundwork to precision-driven and scalable production of medical devices, whereas digital twins and Industry 4.0 technologies are increasing the connectedness of smart hospital settings. At the same time, the recycling of materials, the concept of a circular economy, and the life-cycle assessment (LCA) are emerging as the key to reducing the environmental impact of healthcare production. This theme focuses on the two priorities of pursuing clinical outcomes and responsible innovation by integrating digital intelligence with environmentally friendly practices. The cornerstone of this section will be research that proves the intersection of AI, automation, sustainability, and healthcare-specific applications. The following topics are encouraged in this manuscript:

• AI and machine learning applications in biomedical additive manufacturing
• Robotics and automation for clinical production environments
• Sustainable and green manufacturing practices in healthcare
• Circular economy approaches for medical-grade materials
• Digital twins and Industry 4.0 integration for hospital systems
• Life-cycle assessment of AM-based healthcare devices

Dr. Gurbhej Singh

Dr. Gaurav Tejpal

Dr. Jashanpreet Singh

Prof. Dr. Vikas Sharma

Guest Editors

Keywords: Artificial intelligence, Machine learning, Robotics in healthcare, Industry 4.0, Digital twins, Sustainable manufacturing, Circular economy, Material recycling, Life-cycle assessment, Smart hospitals, Data-driven process optimization, Green technologies