Feature-based modeling for industrial processes in the context of digital twins: A case study of HVOF process. (January 2022) - Ren, Jiangzhuo; Zhou, Tianyu; Rong, Yiming; Ma, Yongsheng; Ahmad, Rafiq
Abstract: Industrial process modeling is currently undergoing a fundamental transformation, leading towards interconnected close-loop twins of models, i.e., the parametrically-controlled real-world physics model, and its corresponding digitalized virtual system model. Between these models, a highly time-sensitive mutual validation mechanism and a coherent and consistent control strategy are applied, which demand complex virtual-and-real world model-based information mapping and synchronization. Thus, this research proposes a semantic conceptual framework for industrial process modeling in the context of digital twins. Based on a hierarchical structure of digital twins, this framework modularizes the modeling process in terms of the semantic information modules of physics in the real-world phenomena, and clarifies inter-module associations and near-real-time data transmission coupled with virtual analysis in CAE environment so that the time-sensitive phenomenon information objects distributed on virtually-separated sub-level physics models can be supported for representing the real-world process comprehensively. Advanced feature concept is adopted to construct the digital models as the basic compositions of any virtual industrial process. The related feature definitions are extended in this work so that the common characteristics in the concept of digital twins could be generically and concisely represented. To validate the modeling method, the digital model of a prototyped High-velocity Oxygen-fuel (HVOF) coating process system was constructed as the case study. The data from the nozzle trajectory, the flame, and the in-flight particle behavior, and the transient thermal performance of the coating layer and substrate were synchronously incorporated for simulating the transient phenomena of the substrate component temperature and coating thickness distribution on the substrate surface. The final simulation result validates that the feature-based digital model is able to comprehensively reflect the real-world scenario on the virtual side. To illustrate how the developed model provides meaningful feedback to the real-world control, a general digital twin setup of the model is given at the end of the case study.