A review of digital twin capabilities, technologies, and applications based on the maturity model

被引:23
作者
Liu, Yang [1 ,2 ]
Feng, Jun [1 ,2 ]
Lu, Jiamin [1 ,2 ]
Zhou, Siyuan [1 ,2 ]
机构
[1] Hohai Univ, Key Lab Water Big Data Technol, Minist Water Resources, Nanjing 211100, Peoples R China
[2] Hohai Univ, Coll Comp Sci & Software Engn, Nanjing 211100, Peoples R China
关键词
Digital twin; DT; Maturity model; Digital twin capabilities; Technologies and applications; BIG DATA; FRAMEWORK; OPTIMIZATION; CHALLENGES; HEALTH; IOT;
D O I
10.1016/j.aei.2024.102592
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The advanced stage of Industry 4.0 is characterized by the integration and interaction between physical and virtual spaces, and Digital Twin (DT) technology, congruent with this vision, has garnered extensive attention and has undergone large-scale implementation. Yet, in the practical implementation of Digital Twin projects, several issues persist: <Circled Digit One> How to formulate reasonable task objectives and action plans before project implementation? <Circled Digit Two> how to determine and assess the development level of the digital twin during project implementation? <Circled Digit Three> How to evaluate the effectiveness of digital twin after project completion and how to enhance improvement in the next steps? Consequently, a methodological model is urgently needed to evaluate the development process of Digital Twins, offering a benchmark for their design, development, and appraisal. To address these issues, this paper introduces a five-level Digital Twin Maturity Model (DTMM), which systematically aligns DT capabilities, phased objectives, and technical requirements within a unified framework, creating a theoretical system capable of assessing DT's developmental level and specifying its construction trajectory. Further, this paper catalogs supporting tools aligned with the technical specifications stipulated in DTMM's functional capabilities, aiding developers in devising implementation strategies. Additionally, it scrutinizes the application status across six DT vertical sectors, conducts maturity evaluations, and confirms the efficacy of the proposed model. The conclusion can be drawn that DT is still in its embryonic phase. This work aspires to assist project managers and public policymakers gain a more objective understanding of Digital Twin, offering references to facilitate their positive development and broader implementation.
引用
收藏
页数:23
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