Conceptualization and Preliminary Development of Statistical Digital Twin and Cyber-Thermophysical System for Advanced Analysis, Monitoring, and Control of the Laser Remelting Process

Laser remelting (LRM) is one of very few universal technologies (i.e., no material removal and no material addition) used in a wide range of manufacturing applications, spanning from surface polishing to functional structuring. Given that LRM is a nonlinear, non-stationary thermodynamic process, its analysis, monitoring, control, and optimization require a comprehensive and fundamental understanding of multiple interlinked laser-material interaction phenomena. Such an understanding is derived from on-line information gained from measurements made during the process by various sensors. Toward this end, this study presents a concept and recent achievement in the development of a statistical digital twin and cyber-thermophysical system towards their use to stabilize, control, and optimize the process. In particular, the digital twin statistically describes the transformation of the initial surface into the LRM topography in terms of thermodynamic transfer functions of remelting and resolidification of surface topography and bulk material. In addition, a cyber-thermophysical system was developed interconnecting the thermodynamic heat-transfer model with the laser beam position, thermal-emission distribution, and overall temperature of the laser-material interaction zone measured and synchronized on-line in space-time position coordinates. The efficiency of the developed cyber-thermophysical system was demonstrated by analyzing the surface formation and process thermodynamics during LRM of H13 tool steel. The preliminary results open new research directions in thermophysics-supported advanced analysis, monitoring, and optimization of LRM, including the implementation of artificial-intelligence methods.