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

Abstract

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 emphasized.

Keywords:

• Makerspaces
• redistributed manufacturing
• community-based production

Notes

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Last mile is a term used in supply chain planning to describe the movement of people and goods from a transportation hub to a final destination in the city (Mikkola and Skjott-Larsen, 2004).

2 Local production systems are defined as a concentration of production activities in a given territorial area in which several participating organizations, most of them small and medium-sized firms work together (Lombardi 2003).

3 Please note only authors cited in the main text appear in the references section. For details of those authors that only appear in the author map (presented in Appendix 1) please refer to the online appendix source files.

4 For further information on the data reduction process the interested reader is recommended to consult Roberts (2000) or Mayring (2014) who discuss the process of building theoretical models from latent factors identified by text analysis. As an analogy, basically we have performed a qualitative version of factor analysis (data reduction) whereby the latent factor causing most variance in the independent variables has been identified. However, this has been done through a qualitative interpretation of the Leximancer software algorithm. This software algorithm identified the latent characteristic linking topics together (from the literature) but content analysis of the literature was needed to support the corresponding identification and association of topics and sub-topics.

5 Technology start up Wonder Workshop created robots Dash & Dot to teach kids to code while they play. Using free apps and a compatible tablet or smartphone, kids learn to code while they make Dash sing, dance and navigate all around house. Sensors on the robot mean that they react to the environment, including children. Further details can be found at: https://www.theguardian.com/technology/2015/sep/07/robots-teach-kids-to-code-dot-dash

Additional information

Funding

Support from the Advanced Manufacturing Supply Chain Initiative [grant no. 35708-233529, ReMediES—Reconfiguring Medicines End-to-End Supply] is gratefully acknowledged. We would also like to acknowledge the research support of Callum Neal.

Notes on contributors

Patrick A. Hennelly

Patrick is a research assistant at the Centre for International Manufacturing, Institute for Manufacturing, University of Cambridge. He is completing a PhD in management from Leeds University Business School, his PhD focuses on relationship formation in the UK offshore wind sector. He has an MSc (Distinction) in logistics and supply chain management from the University of Hull Logistics Institute. He has been guest editor for a special issue in Business Process Management Journal. His research interests lie in the areas of supply chain management, distributed manufacturing and digitalisation.

Jagjit Singh Srai

Jag is Head of the Centre for International Manufacturing, Institute for Manufacturing, University of Cambridge where he completed his PhD in Engineering, Manufacturing and Management. His research work and that of his group involves working closely with Industry in the analysis, design and operation of international production, supply and service networks. Current research areas include global value network analysis, service network integration and the development of new forms of supply network that support emerging industries. Research projects are cross-sector in nature but include supply network and industry transformations linked to specific challenges within Pharmaceuticals, Food, Automotive and Aerospace.

Gary Graham

Gary is an Associate Professor of Operations and Supply Chain Management and a co-director of the Cities themed Design and Production Group. He is a visiting research scholar at The Massachusetts Institute of Technology’s Centre for Transport and Logistics. He founded and co-ordinates the Smart Cities and Economic Resilience Network (a membership of 60 international scholars, manufacturers, supply chain managers and community workers (http://www.fccrnet.org/)). His work focuses on smart city manufacturing, productivity, localization, smaller companies and democratising the means of production. He has research collaboration on “Distributed Manufacturing” and “Industry 4.0” with the Institute for Manufacturing, University of Cambridge.

Royston Meriton

Dr Roy Meriton is a Lecturer in Innovation and Entrepreneurship, teaching modules on innovation management and research methods. Roy's research interests centre on disruptive technologies, such as Big Data and IoTs, as input resources to a firm's competitive posture.

Mukesh Kumar

Mukesh Kumar is a University lecturer at the Department of Engineering, University of Cambridge. He is based at the Institute for Manufacturing and leading research on industrial resilience. His research has included food product safety management from developed and developing country perspectives, risk evaluation in pharmaceutical supply, and environment sustainability assessment in global supply networks in four sectors – food, pharmaceuticals, automotive and aerospace. His research continues to focus on sustainability and resilience but closely related to the emerging manufacturing paradigm of “Distributed Manufacturing”.