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Overview of predictive maintenance based on digital twin technology

Heliyon · 2023 · Vol. 9(4) · pp. e14534–e14534
Zhong DongZhelei XiaYi‐An ZhuJun-Hua Duan

Abstract

The upgrade and development of manufacturing industry makes predictive maintenance more and more important, but the traditional predictive maintenance can not meet the development needs in many cases. In recent years, predictive maintenance based on digital twin has become a research hotspot in the manufacturing industry field. Firstly, this paper introduces the general methods of digital twin technology and predictive maintenance technology, analyzes the gap between them, and points out the importance of using digital twin technology to realize predictive maintenance. Secondly, this paper introduces the predictive maintenance method based on digital twin (PdMDT), introduces its characteristics, and gives its differences from traditional predictive maintenance. Thirdly, this paper introduces the application of this method in intelligent manufacturing, power industry, construction industry, aerospace industry, shipbuilding industry, and summarizes the latest development in these fields. Finally, the PdMDT puts forwards a reference framework in manufacturing industry, the framework describes the specific implementation process of equipment maintenance, and gives an example of industrial robot using the framework, and discusses the limitations, challenges and opportunities of the PdMDT.

Digital Transformation in IndustryManufacturing Process and OptimizationTechnology Assessment and ManagementPredictive maintenanceShipbuildingEngineeringField (mathematics)Manufacturing engineeringPredictive analyticsIndustry 4.0ManufacturingAerospaceComputer science

Funding

  • Key Technologies Research and Development Program
  • Key Research and Development Projects of Shaanxi Province
Citations
255
FWCI
51.66
field-weighted impact
References
71
Percentile
100%
vs. same field & year
Citations per year
References
A review on machinery diagnostics and prognostics implementing condition-based maintenance
Mechanical Systems and Signal Processing · 2005 · 4,389 citations
Digital Twin in Industry: State-of-the-Art
IEEE Transactions on Industrial Informatics · 2019 · 3,580 citations
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