Digital Twin Driven Green Material Optimal-Selection towards Sustainable Manufacturing

Abstract

Green material optimal-selection in product design is a key issue for realizing sustainable manufacturing. In order to improve the accuracy and efficiency for green material optimal-selection in product, a new method driven by digital twin (DT) is proposed. In this method, an optimal evolvement model which is an evolving and high-fidelity digital twin of the physical product is first established. Then the collected cyber and physical data are fused. Based on the mode and fused data, the performance of green materials selection is simulated and evaluated. Finally, a case study on laptop design is given out to illustrate the proposed method.