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IDENTIFY CRITICAL DATA DURING PRODUCT CUSTOMISATION – A CASE STUDY OF ORTHOSES FABRICATION

Part of: Design Support Tools

Published online by Cambridge University Press:  11 June 2020

X. Tan ,
W. Chen ,
J. Cao  and
S. Ahmed-Kristensen
X. Tan*
Affiliation:
Imperial College London, United Kingdom
W. Chen
Affiliation:
Xuzhou Central Hospital, China
J. Cao
Affiliation:
Xuzhou Central Hospital, China
S. Ahmed-Kristensen
Affiliation:
Royal College of Art, United Kingdom
*
*xinyang.tan14@imperial.ac.uk

Abstract

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Big data provides high volume of data to inform product customisation. Understanding which data is relevant remains a challenge. A method is proposed to identify relevant data to inform data-driven customisation. A case study regarding customisation of orthoses was conducted. Verbal protocol analysis was employed to extract time spent on major fabrication phases. Data related to patients, therapists and fabrication time was analysed. Results showed that the number of stabilised joints, experience of therapists and whether the design is for in- or out-patient are key factors for customisation.

Keywords

human behaviourprotocol analysisdata-driven designhealthcare designcustomisation
Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 413 - 422
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), 2020. Published by Cambridge University Press

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