A Delphi-based risk analysis — Identifying and assessing future challenges for supply chain security in a multi-stakeholder environment

Purpose During the COVID-19 pandemic, the three-dimensional (3D) printing community is actively participating to address the supply chain gap of essential medical supplies such as face masks, face shields, door adapters, test swabs and ventilator valves. This paper aims to present a comprehensive study on the role of 3D printing during the coronavirus (COVID-19) pandemic, its safety and its challenges. Design/methodology/approach This review paper focuses on the applications of 3D printing in the fight against COVID-19 along with the safety and challenges associated with 3D printing to fight COVID-19. The literature presented in this paper is collected from the journal indexing engines including Scopus, Google Scholar, ResearchGate, PubMed, Web of Science, etc. The main keywords used for searches were 3D printing COVID-19, Safety of 3D printed parts, Sustainability of 3D printing, etc. Further possible iterations of the keywords were used to collect the literature. Findings The applications of 3D printing in the fight against COVID-19 are 3D printed face masks, shields, ventilator valves, test swabs, drug deliveries and hands-free door adapters. As most of these measures are implemented hastily, the safety and reliability of these parts often lacked approval. The safety concerns include the safety of the printed parts, operators and secondary personnel such as the workers in material preparation and transportation. The future challenges include sustainability of the process, long term supply chain, intellectual property and royalty-free models, etc. Originality/value This paper presents a comprehensive study on the applications of 3D printing in the fight against COVID-19 with emphasis on the safety and challenges in it.

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Hydrological Layered Dialysis Research on Supply Chain Financial Risk Prediction under Big Data Scenario

Discrete Dynamics in Nature and Society ◽

10.1155/2018/3259858 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9

Author(s):

Jia Liu ◽

Shiyong Li ◽

Xiaoxia Zhu

Keyword(s):

Risk Management ◽

Big Data ◽

Supply Chain ◽

Risk Analysis ◽

Risk Prediction ◽

Financial Institutions ◽

Surface Runoff ◽

Financial Risk ◽

Supply Chain Finance ◽

Runoff Model

In recent years, internet development provides new channels and opportunities for small- and middle-sized enterprises’ (SMEs) financing. Supply chain finance is a hot topic in theoretical and practical circles. Financial institutions transform materialized capital flows into online data under big data scenario, which provides networked, precise, and computerized financial services for SMEs in the supply chain. By drawing on the risk management theory in economics and the distributed hydrological model in hydrology, this paper presents a supply chain financial risk prediction method under big data. First, we build a “hydrological database” used for the risk analysis of supply chain financing under big data. Second, we construct the risk identification models of “water circle model,” “surface runoff model,” and “underground runoff model” and carry on the risk prediction from the overall level (water circle). Finally, we launch the supply chain financial risk analysis from breadth level (surface runoff) and depth level (underground runoff); moreover, we integrate the analysis results and make financial decisions. The results can enrich the research on risk management of supply chain finance and provide feasible and effective risk prediction methods and suggestions for financial institutions.

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