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CROWDSOURCING ENGINEERING DESIGN PROBLEMS: LEARNING FROM EXPERIENCES

Published online by Cambridge University Press:  19 June 2023

Chijioke C. Obieke ,
Jelena Milisavljevic-Syed  and
Ji Han
Chijioke C. Obieke
Affiliation:
University of Liverpool;
Jelena Milisavljevic-Syed
Affiliation:
Cranfield University;
Ji Han*
Affiliation:
University of Exeter
*
Han, Ji, University of Exeter, United Kingdom, [email protected]

Abstract

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The availability of digital data in the fourth industrial revolution brings different trends with new opportunities and challenges for the engineering design community. As an opportunity, these trends would impact engineering design. However, the challenge is finding applications for these trends in engineering design. Crowdsourcing is one of the trends inspired by digital data. It is outsourcing an individually performed task to be mass-performed. This paper explores the application of crowdsourcing in identifying engineering design problems. Identifying an engineering design problem is an aspect of engineering design considered challenging but necessary for inventions. Secondary data from 63 invention-related cases and an interview with a renowned UK inventor are presented. The data contains scenarios on how the engineering design problems solved to qualify for a UK patent grant or application are identified. Lessons from the case studies are presented and discussed, especially regarding crowdsourcing engineering design problems. These seem to be promising ways of supporting the identification of new engineering design problems with inventive benefits once solved.

Keywords

Design engineeringCrowdsourcingEarly design phasesDigital DataProblem-exploring
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1107 - 1116
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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