New Paradigm of Data-Driven Smart Customisation through Digital Twin

被引:85
作者
Wang, Xingzhi [1 ]
Wang, Yuchen [1 ]
Tao, Fei [2 ]
Liu, Ang [1 ]
机构
[1] Univ New South Wales, Fac Engn, Sch Mech & Mfg Engn, Sydney, NSW 2052, Australia
[2] Behang Univ, Sch Automat Sci & Elect Engn, Beijing 100083, Peoples R China
基金
美国国家科学基金会;
关键词
Digital twin; Customisation; Smart manufacturing; Personalisation; Product Service system; MANUFACTURING SYSTEMS; BIG DATA; MANAGEMENT; LOGISTICS; STRATEGY; SERVICE; DESIGN;
D O I
10.1016/j.jmsy.2020.07.023
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Big data is one of the most important resources for the promotion of smart customisation. With access to data from multiple sources, manufacturers can provide on-demand and customised products. However, existing research of smart customisation has focused on data generated from the physical world, not virtual models. As physical data is constrained by what has already occurred, it is limited in the identification of new areas to improve customer satisfaction. A new technology called digital twin aims to achieve this integration of physical and virtual entities. Incorporation of digital twin into the paradigm of existing data-driven smart customisation will make the process more responsive, adaptable and predictive. This paper presents a new framework of data driven smart customisation augmented by digital twin. The new framework aims to facilitate improved collaboration of all stakeholders in the customisation process. A case study of the elevator industry illustrates the efficacy of the proposed framework.
引用
收藏
页码:270 / 280
页数:11
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