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.
Editors
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Xiangfan Chen, PhD
Assistant Professor, School of Manufacturing Systems and Networks, Arizona State University, USA
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Wenzhuo Wu, PhD
Professor, School of Industrial Engineering, Purdue University, USA
The Collection will publish original research Articles, Reviews, Perspectives and Comments (full details on content types can be found here). Papers will be published in npj Advanced Manufacturing as soon as they are accepted and then collected together and promoted on the Collection homepage. All Guest Edited Collections are associated with a call for papers and are managed by one or more of our Editorial Board Members and the journal's Editors.
This Collection welcomes submissions from all authors – and not by invitation only – on the condition that the manuscripts fall within the scope of the Collection and of npj Advanced Manufacturing more generally. See our editorial process page for more details.
All submissions are subject to the same peer review process and editorial standards as regular npj Advanced Manufacturing articles, including the journal’s policy on competing interests. The Guest Editors have no competing interests with the submissions, which they handle through the peer-review process. The peer review of any submissions for which the Guest Editors have competing interests is handled by another Editorial Board Member who has no competing interests. See our Collections guidelines for more details.
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