A high-fidelity digital twin approach for the optimisation of fluid jet polishing process

Chao Liu*, Chunjin Wang, Zili Zhang, Pin Lyu, Chi Fai Cheung

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


Fluid Jet Polishing (FJP) is an Ultra-Precision Machining (UPM) technology for super-fine finishing of small and complex components. FJP has distinctive advantages compared to other polishing methods, including high polishing accuracy, no heat generation, no tool wear, applicability for various types of materials, and suitability for various freeform surfaces. Nevertheless, previous research work on FJP focuses mainly on theoretical modelling and simulation of the polishing mechanisms with experimental validations, a large amount of process uncertainties happened during the polishing process have been overlooked. These uncertainties could cause variations of the surface quality of workpieces in terms of material removal rate and surface roughness. Recent advancements of Digital Twin (DT) technology have shown great potential in addressing this issue. However, high-fidelity DT for FJP has not been investigated to date. In this paper, we propose a novel high-fidelity DT approach for the optimisation of FJP process. First, related research on FJP and DT is reviewed to identify the limitations of the existing approaches. Second, we propose a conceptual framework of the high-fidelity DT for FJP process. Third, the key enabling technologies and major challenges for the development of the high-fidelity DT are identified and discussed. Finally, a conceptual application scenario of the in-process control optimisation for FJP of freeform surfaces is presented. This work attempts to integrate smart manufacturing technologies into FJP process and will contribute to the theoretical development of high-fidelity DT for various UPM technologies.

Original languageEnglish
Pages (from-to)101-106
Number of pages6
JournalProcedia CIRP
Publication statusPublished - 26 May 2022
Event55th CIRP Conference on Manufacturing Systems, CIRP CMS 2022 - Lugano, Switzerland
Duration: 29 Jun 20221 Jul 2022

Bibliographical note

This is an open access article under the CC BY-NC-ND license 4.0

Funding Information:
This research work was partially supported by the National Natural Science Foundation of China (Project No. 52105534) and the State Key Laboratory of Ultra-precision Machining Technology and the Research Office of The Hong Kong Polytechnic University (Project codes: BBX5 and BBX7).


  • digital twin
  • fluid jet polishing
  • smart manufacturing
  • ultra-precision machining


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