Abstract
Maker Networks indicate how society organizes itself to overcome significant challenges, such as the lack of Personal Protective Equipment (PPE) observed during the COVID-19 pandemic. We analyze initiatives that produced PPE for frontline health staff to propose design guidelines for implementing RDM-Maker Networks: networks of people and organizations in the Maker Movement that collaboratively produce goods or services organized in a redistributed manufacturing (RDM) model. This paper has two main results: five Maker Networks in Brazil analyzed in terms of their RDM features and the subsequent design guidelines. We selected cases through several criteria like their location and the type of one of their nodes. Those criteria also represent limitations that further works can address.
Highlights
Recent works on Maker Movement have claimed its influence on economic development and innovative solutions generation (Chen & Wu, 2017)
The study relies on literature from two searches: one focusing on Maker Movement and the other dealing with Redistributed Manufacturing (RDM)
We focused on the Brazilian region with the highest number of initiatives (Olabi, 2020), the Southeast, which happens to be the region with the highest number of cases of COVID-19 (Ministério da Saúde, 2020) as of the date of this research
Summary
Recent works on Maker Movement have claimed its influence on economic development and innovative solutions generation (Chen & Wu, 2017). There are works associating makers to production dynamics like peer production (Kohtala & Bosqué, 2014; Menichinelli, Bianchini, Carosi, & Maffei, 2017; Wolf & Troxler, 2016; Wolf, Troxler, Kocher, Harboe, & Gaudenz, 2014) and social manufacturing (Hamalainen & Karjalainen, 2017; Hirscher, Mazzarella, & Fuad-Luke, 2019; Yang & Jiang, 2019) It has not yet described the production model of cases where a network of people and organizations inserted in the Maker Movement are collaboratively producing some good or delivering some service in the context of redistributed manufacturing. We started to observe similar collaborative networks (Manzini, 2012), which became a good set of cases to study
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