Collection 

Smart Manufacturing for Biomedical Applications

Submission status
Open
Submission deadline

Smart manufacturing, integrating AI, IoT, robotics, and data analytics, serves as a cornerstone for enhancing production processes, particularly in the biomedical sector. It significantly boosts precision and efficiency through automation, a critical requirement in an industry where accuracy is paramount. Additionally, it enables the customization of medical devices and pharmaceuticals, meeting individual patient needs more effectively. Simultaneously, it ensures strict adherence to industry standards, elevating quality assurance and concurrently reducing operational costs.

Recent advancements in smart manufacturing for biomedical purposes concentrate on pivotal domains. AI innovation is reshaping healthcare by bolstering drug discovery, diagnostics, and personalized medicine. Furthermore, 3D printing empowers tailored solutions such as bespoke implants and prosthetics, propelling the realm of patient-specific treatments. IoT integration within medical devices enables remote monitoring and real-time data analysis, augmenting device functionality and patient care. Additionally, leveraging data analytics on biological and clinical data drives the paradigm of precision medicine, facilitating personalized treatment approaches.

This convergence of cutting-edge technologies defines the progression in biomedical smart manufacturing. Their cohesive integration constructs interconnected systems centered on data, not only optimizing production but also broadening the horizons and enhancing the caliber of biomedical products and treatments. Ultimately, this progression significantly influences improved patient care and outcomes.

Moreover, we welcome submissions addressing 'Smart manufacturing for biomedical applications' to undergo a rigorous peer-review process adhering to the editorial standards of npj Advanced Manufacturing. Guest Editor overseeing submissions affirm no conflicts of interest in their oversight.

Submit manuscript
Manuscript editing services
Team of Research Scientists Working On Computer, with Medical Equipment, Analyzing Blood and Genetic Material Samples with Special Machines in the Modern Laboratory.

Editors

  • Xiangfan Chen, PhD

    Assistant Professor, School of Manufacturing Systems and Networks, Arizona State University, USA

Articles will be displayed here once they are published.