3D Printing in COVID-19: Productivity Estimation of the Most Promising Open Source Solutions in Emergency Situations
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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2020-06-09
Major/Subject
Mcode
Degree programme
Language
en
Pages
13
Series
APPLIED SCIENCES, Volume 10, issue 11
Abstract
The COVID-19 pandemic has caused a surge of demand for medical supplies and spare parts, which has put pressure on the manufacturing sector. As a result, 3D printing communities and companies are currently operating to ease the breakdown in the medical supply chain. If no parts are available, 3D printing can potentially be used to produce time-critical parts on demand such as nasal swabs, face shields, respirators, and spares for ventilators. A structured search using online sources and feedback from key experts in the 3D printing area was applied to highlight critical issues and to suggest potential solutions. The prescribed outcomes were estimated in terms of cost and productivity at a small and large scale. This study analyzes the number and costs of parts that can be manufactured with a single machine within 24 h. It extrapolates this potential with the number of identical 3D printers in the world to estimate the global potential that can help practitioners, frontline workers, and those most vulnerable during the pandemic. It also proposes alternative 3D printing processes and materials that can be applicable. This new unregulated supply chain has also opened new questions concerning medical certification and Intellectual property rights (IPR). There is also a pressing need to develop new standards for 3D printing of medical parts for the current pandemic, and to ensure better national resilience.Description
Keywords
coronavirus, additive manufacturing, rapid manufacturing, COVID-19, SARS-CoV-2, 3D printing, supply chain disruption, bridge manufacturing, PPE
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Citation
Salmi, M, Akmal, J S, Pei, E, Wolff, J, Jaribion, A & Haghighat Khajavi, S 2020, ' 3D Printing in COVID-19: Productivity Estimation of the Most Promising Open Source Solutions in Emergency Situations ', Applied Sciences, vol. 10, no. 11, 4004 . https://doi.org/10.3390/app10114004
