A new quantitative digital twin maturity model for high-end equipment. (February 2023)

• Record Type: Journal Article
• Authors: Hu, Weifei; Fang, Jianhao; Zhang, Tongzhou; Liu, Zhenyu; Tan, Jianrong
• Is Part Of: Journal of manufacturing systems. Volume 66(2023)
• Page Start: 248
• Page End: 259
• Publication Date: 2023-02
• Subjects: Digital twin -- High-end equipment -- Maturity model -- Analytic hierarchy process -- Matter-element extension method; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2022.12.012
• Languages: English
• ISSNs: 0278-6125

Abstract

Abstract: Digital twins (DTs) have shown great potential in both academia and industry due to their ability to interconnect and integrate physical and virtual worlds. A DT maturity model for high-end equipment is important to accurately evaluate the maturity level of DT and further develop an advanced DT. This paper is one of the early endeavours, to the best of the authors' knowledge, to provide a new DT maturity model for high-end equipment combining qualitative and quantitative analysis. The qualitative analysis of the DT maturity model includes a comparison and assessment of 3 dimensions and 27 rubrics for different DTs of high-end equipment. In addition, 6 maturity levels and their definitions for each rubric are proposed for maturity scoring. The quantitative analysis of the DT maturity model is conducted based on an analytic hierarchy process and a matter-element extension method, which can be used to provide improvement advice according to the rubric importance and its improvement difficulties. The proposed DT maturity model is applied to evaluate the maturity of DTs of three high-end equipment, including underground engineering equipment, a large-scale wind turbine, and an industrial shop-floor. The evaluated maturity results could be used to elevate the maturity of DT by improving rubrics with high significance, low level, and low improvement difficulty. Highlights: Qualitative evaluation of DT maturity considers 3 main dimensions and 27 rubrics. Quantitative analysis of DT maturity provides rubrics importance and improvement difficulties. DT maturity could be advanced by improving rubrics with high significance, low level, and low improvement difficulty.