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Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies
Significant public health emergencies greatly impact the global supply chain system of production and cause severe shortages in personal protective and medical emergency supplies. Thus, rapid manufacturing, scattered distribution, high design degrees of freedom, and the advantages of the low thresho...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032952/ https://www.ncbi.nlm.nih.gov/pubmed/33842427 http://dx.doi.org/10.3389/fpubh.2021.657276 |
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author | He, Jianjia Liu, Gang Mai, Thi Hoai Thuong Li, Ting Ting |
author_facet | He, Jianjia Liu, Gang Mai, Thi Hoai Thuong Li, Ting Ting |
author_sort | He, Jianjia |
collection | PubMed |
description | Significant public health emergencies greatly impact the global supply chain system of production and cause severe shortages in personal protective and medical emergency supplies. Thus, rapid manufacturing, scattered distribution, high design degrees of freedom, and the advantages of the low threshold of 3D printing can play important roles in the production of emergency supplies. In order to better realize the efficient distribution of 3D printing emergency supplies, this paper studies the relationship between supply and demand of 3D printing equipment and emergency supplies produced by 3D printing technology after public health emergencies. First, we fully consider the heterogeneity of user orders, 3D printing equipment resources, and the characteristics of diverse production objectives in the context of the emergent public health environment. The multi-objective optimization model for the production of 3D printing emergency supplies, which was evaluated by multiple manufacturers and in multiple disaster sites, can maximize time and cost benefits of the 3D printing of emergency supplies. Then, an improved non-dominated sorting genetic algorithm (NSGA-II) to solve the multi-objective optimization model is developed and compared with the traditional NSGA-II algorithm analysis. It contains more than one solution in the Pareto optimal solution set. Finally, the effectiveness of 3D printing is verified by numerical simulation, and it is found that it can solve the matching problem of supply and demand of 3D printing emergency supplies in public health emergencies. |
format | Online Article Text |
id | pubmed-8032952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80329522021-04-10 Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies He, Jianjia Liu, Gang Mai, Thi Hoai Thuong Li, Ting Ting Front Public Health Public Health Significant public health emergencies greatly impact the global supply chain system of production and cause severe shortages in personal protective and medical emergency supplies. Thus, rapid manufacturing, scattered distribution, high design degrees of freedom, and the advantages of the low threshold of 3D printing can play important roles in the production of emergency supplies. In order to better realize the efficient distribution of 3D printing emergency supplies, this paper studies the relationship between supply and demand of 3D printing equipment and emergency supplies produced by 3D printing technology after public health emergencies. First, we fully consider the heterogeneity of user orders, 3D printing equipment resources, and the characteristics of diverse production objectives in the context of the emergent public health environment. The multi-objective optimization model for the production of 3D printing emergency supplies, which was evaluated by multiple manufacturers and in multiple disaster sites, can maximize time and cost benefits of the 3D printing of emergency supplies. Then, an improved non-dominated sorting genetic algorithm (NSGA-II) to solve the multi-objective optimization model is developed and compared with the traditional NSGA-II algorithm analysis. It contains more than one solution in the Pareto optimal solution set. Finally, the effectiveness of 3D printing is verified by numerical simulation, and it is found that it can solve the matching problem of supply and demand of 3D printing emergency supplies in public health emergencies. Frontiers Media S.A. 2021-03-26 /pmc/articles/PMC8032952/ /pubmed/33842427 http://dx.doi.org/10.3389/fpubh.2021.657276 Text en Copyright © 2021 He, Liu, Mai and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health He, Jianjia Liu, Gang Mai, Thi Hoai Thuong Li, Ting Ting Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies |
title | Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies |
title_full | Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies |
title_fullStr | Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies |
title_full_unstemmed | Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies |
title_short | Research on the Allocation of 3D Printing Emergency Supplies in Public Health Emergencies |
title_sort | research on the allocation of 3d printing emergency supplies in public health emergencies |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032952/ https://www.ncbi.nlm.nih.gov/pubmed/33842427 http://dx.doi.org/10.3389/fpubh.2021.657276 |
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