2024

Zhang Xi; Yang Ye; Zhang Xin; Hu Youmin; Wu Huapeng; Li Ming; Handroos Heikki; Wang Haifeng; Wu Bo

The digital twin (DT) is recognized as a promising technology for achieving enhanced monitoring, control, and prediction of physical systems, contributing to increased reliability and effectiveness. While most researchers have concentrated on developing DTs for shop-floor and machine tools, there has been limited attention given to human operators. Only a few researchers have recognized that building a human DT is critical to achieving human-centric production. we propose a hybrid modeling approach that combines a mechanism model and a time-series forecasting model. This comprehensive full-lifecycle worker DT model is designed for production activities. Subsequently, we employ a discrete-event simulation model to amalgamate the worker DT with an industrial robot DT. The modular and multi-level modeling methodology is employed to enhance the efficiency of system reconstruction. Finally, we illustrate the modeling process and functions using a washing machine assembly line as an example. The presented model facilitates the creation of new workers’ training plans, demonstrating the practical application of the proposed method. This novel approach to modeling workers’ DT in manufacturing not only supports the development of a more accurate DT production system but also offers versatility for application in various contexts.