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Do makerspaces represent scalable production models of community-based redistributed manufacturing?

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journal contribution
posted on 2018-01-18, 16:39 authored by Patrick Hennelly, Jag Srai, Gary Graham, Roy Meriton, Mukesh Kumar
This research explores the development of local community-based “makerspaces” as potential scalable forms of redistributed manufacturing (RDM). Makerspaces are rapidly emerging in post-industrial economies and have been identified as a catalyst of local regeneration in urban areas. However, their role in local production systems is limited. There is a gap in the literature, with respect to the evolution of makerspaces and their productive contribution. The purpose of this paper therefore is to identify, classify and examine the different types of makerspaces. Our focus is on the implementation characteristics that enable industrial production activity to take place. First, we used Leximancer (to identify from the literature) three types of makerspace. Second, we then identify five RDM implementation characteristics. The characteristics were integrated together to form the RDM-makerspace implementation model. Third, case studies were purposively selected to test and advance this model. They were subsequently classified as a Type 1 (educational), Type 2 (design) or Type 3 (production) makerspace. Only one of the case studies was classified as a fully evolved Type 3 production space. The findings concur with the literature that makerspaces tend to be primarily Type 1 or Type 2. Finally, the contribution to local production theory is emphasised.

History

School

  • Loughborough University London

Published in

Production Planning and Control

Volume

30

Issue

7

Pages

540 - 554

Citation

HENNELLY, P. ... et al, 2019. Do makerspaces represent scalable production models of community-based redistributed manufacturing?. Production Planning and Control, 30 (7), pp.540-554.

Publisher

© Taylor & Francis

Version

  • AM (Accepted Manuscript)

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning and Control on 15 May 2019, available online: http://www.tandfonline.com/10.1080/09537287.2018.1540056.

Acceptance date

2017-11-29

Publication date

2019-05-15

ISSN

0953-7287

eISSN

1366-5871

Language

  • en

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