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Design for replicability in open-source distributed manufacturing for low-resource settings: a case study of two-piece 3D-printed forearm crutches

Romani, A.; Nansubuga, R. K.; Mottaghi, M.; Munang, D.; Bow Pearce, E.; Viswanathan, P.; Jenkyn, T.; Loubani, T.; Reeves, J. M.; Pearce, J. M.

2026-02-17 emergency medicine
10.64898/2026.02.13.26345756 medRxiv
Show abstract

Distributed manufacturing of open-source hardware shows potential to offer accessible, affordable, and customizable solutions for users in low-resource contexts. Their real-world adoption, however, depends not only on the availability of openly shared designs but also on their replicability when fabricated in different local contexts. This work investigates the replicability of open-source hardware through a practical design-driven approach, using the development and experimental evaluation of a two-piece open-source forearm crutch as a case study. Replicability was considered from early-stage design and evaluated by introducing controlled variations from distributed manufacturing contexts, e.g., material feedstock, manufacturing equipment, and fabrication strategies. Four batches of crutches were fabricated and assembled, using virgin and recycled filaments on small- and large-format 3D printers. After the qualitative evaluation, mechanical static load testing was performed following ISO 11334:2007, together with economic analysis. Comparable mean load-bearing and consistent failure behavior were achieved across batches, making them suitable for use in pairs. Limited cost variability was achieved, supporting repairability and product lifecycle extension. Beyond the specific case study, replicability of open-source hardware needs to be considered as an early-stage design constraint by developing products that allow for variability from local contexts and by including product-specific approaches to assess replicability during development.

Published in Disability and Rehabilitation: Assistive Technology · not in our set (fewer than 10 published preprints to learn from) · training set

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