A Digital Twin-Based Approach for Quality Control and Optimization of Complex Product Assembly

Abstract

To address the problems caused by low ability of quality analysis and decision-making in the process of complex product assembly, in this paper, we proposed a digital twin-based approach for quality control and optimization of complex product assembly, by providing a digital twin system to realize the timely and precisely interactive mapping between the physical world and digital world. Specifically, a quality control and optimization mechanism is presented, which provides the theoretical support to the realization of the digital twin-based approach. A data-driven quality control model is introduced to solve the optimization problem by considering the panoramic assembly quality data. A digital twin system for complex product assembly is elaborated by providing detailed deployment and implementation procedures, which includes (1) building of the digital entity of an assembly line, (2) real-time online sensing in multi-source heterogeneous environment, (3) real-time simulation of equipment and assembly process, (4) realization of the intelligent production scheduling under uncertainty conditions, and (5) dynamical adjustment of the assembly process. Finally, the paper presents the validation results considering the practical applications of the proposed approach in real industrial fields.