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Title: A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment
Authors: Zheng, Pai
Xu, Xun
Chen, Chun-Hsien
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Zheng, P., Xu, X. & Chen, C. (2020). A data-driven cyber-physical approach for personalised smart, connected product co-development in a cloud-based environment. Journal of Intelligent Manufacturing, 31(1), 3-18.
Project: RCA-16/434
Journal: Journal of Intelligent Manufacturing
Abstract: The rapid development of information and communication technology enables a promising market of information densely product, i.e. smart, connected product (SCP), and also changes the way of user–designer interaction in the product development process. For SCP, massive data generated by users drives its design innovation and somehow determines its final success. Nevertheless, most existing works only look at the new functionalities or values that are derived in the one-way communication by introducing novel data analytics methods. Few work discusses about an effective and systematic approach to enable individual user innovation in such context, i.e. co-development process, which sets the fundamental basis of the prevailing concept of data-driven design. Aiming to fill this gap, this paper proposes a generic data-driven cyber-physical approach for personalised SCP co-development in a cloud-based environment. A novel concept of smart, connected, open architecture product is hence introduced with a generic cyber-physical model established in a cloud-based environment, of which the interaction processes are enabled by co-development toolkits with smartness and connectedness. Both the personalized SCP modelling method and the establishment of its cyber-physical product model are described in details. To further demonstrate the proposed approach, a case study of a smart wearable device (i.e. i-BRE respiratory mask) development process is given with general discussions.
ISSN: 0956-5515
DOI: 10.1007/s10845-018-1430-y
Schools: School of Electrical and Electronic Engineering 
School of Mechanical and Aerospace Engineering 
Research Centres: Delta-NTU Corporate Laboratory 
Rights: © 2018 Springer Science+Business Media, LLC, part of Springer Nature. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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