Additive Manufacturing for Localized Medical Parts Production: A Case Study

Victor Verboeket, Siavash Haghighat Khajavi, Harold Krikke, Mika Salmi, Jan Holmström

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Centralized supply chains (SCs) are prone to disruption, which makes them a risky choice for medical equipment production. Additive manufacturing (AM) allows for production localization and improvements in SC resilience. However, the comparative competitiveness of a localized SC from the time and cost perspective is still unclear. In this study, we investigate the competitiveness of localized medical part AM SCs against centralized ones by analyzing the responsiveness and cost of each SC. We utilize a real-world case study in which an AM service provider supplies medical parts to university medical centers in the Netherlands to construct six scenarios. We also develop a thorough empirical cost formulation for both central and local AM of patient-specific medical parts. The results of scenario analysis show that when utilizing the currently available AM technology, localized SC configurations significantly reduce the delivery time from about 54 to 27h, but at a 4.3-fold higher cost. Hence, we illustrate that the cost difference between the localized and centralized scenarios can be reduced when state-of-the-art AM machines are utilized, demand volumes increase, and the distances between the SC network nodes expand. Moreover, our scenario analysis confirms that the cost of the measures taken to prevent dust dispersion associated with powder-bed fusion AM has a major impact on the total cost of localized AM SCs for medical parts. The results of this study contribute to the understanding of the relevant factors in deciding whether central or localized SC configurations can be used in the AM production of medical parts. Furthermore, this study provides managerial insights for decision-makers at governments and hospitals as well as AM service providers and AM equipment manufacturers.
Original languageEnglish
Article number9343813
Pages (from-to)25818 - 25834
Number of pages17
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021
MoE publication typeA1 Journal article-refereed

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