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

Abstract

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.