Abstract In human-machine collaborative assembly, assembly tasks require the simultaneous use of multiple assembly resources, including human operators and machines. The assembly tasks are modeled as multi-processor jobs, while the corresponding assembly resources are represented by identical parallel machines. In Digital Twin Assembly (DTA), the virtual assembly system continuously synchronizes the state of the physical assembly system, including resource availability and task progress. Once the synchronized state differs from the one under which the original due dates and schedule were determined, the originally assigned due dates and the corresponding schedule are no longer appropriate. Therefore, each synchronization event necessitates the joint re-optimization of due date assignment and scheduling, with due dates treated as decision variables rather than predetermined parameters. Motivated by this setting, this paper studies a multi-processor job scheduling problem with due date assignment, where each job requires multiple identical machines and all jobs share identical processing times. The objective is to minimize the total weighted number of tardy jobs together with due date assignment costs. For the common due date case, the problem is shown to be equivalent to a scheduling problem with rejection, and an optimal solution procedure is developed by partitioning jobs into accepted and rejected sets and determining the best schedule and due date for each partition. For the special case with two machines, a more efficient solution is obtained. For the unrestricted due date case, we derive the optimal due date assignment for any given schedule and develop a corresponding optimal solution method, with a simplified version also available when only two machines are involved.

Abstract Assembly connection has always been a weak link in high-end equipment such as aero engines and aerospace equipment. However, due to the strong closed nature of the assembly interface, the problems of ‘unmeasurable’ and ‘inaccurate measurement’ of the interface mechanical state have become increasingly prominent. Meanwhile, the current assembly process relies heavily on manual experience, leading to frequent problems of ‘uncontrollable’ connection quality in assembly, which is difficult to meet the development requirements of high performance and high reliability of the new generation of aerospace equipment. Therefore, an attempt is made to explore the establishment of a digital twin evaluation and control system for the mechanics of assembly connection interfaces, providing research ideas for improving high-performance assembly.

Abstract In the manufacturing field of aeronautical and aerospace products, with the rapid advancement of ultra-precision machining technology, the machining accuracy and consistency of components have been significantly improved, and the role of assembly in ensuring the overall performance of finished products has become increasingly prominent. Taking array antennas as an example, their functional structures exhibit characteristics such as high density, high precision, cross-scale integration, and strong mechanical-electromagnetic coupling, and their assembly quality has become one of the bottlenecks restricting the service performance of array antennas. Similarly, the assembly accuracy and its ground-orbit consistency of space deployable mechanisms are key bottlenecks that limit the high-performance service of spacecraft functional payloads.To address this issue, targeting the assembly of typical aeronautical and aerospace products, this study carries out research on assembly quality prediction and regulation technology and its application. It mainly includes three key technologies: digital twin technology for different scales of the assembly process, assembly accuracy prediction technology oriented to stress uniformity, and assembly process decision-making and optimization technology. On this basis, a digital twin assembly system has been independently designed and developed, realizing three-dimensional visual monitoring of the product assembly process.

Abstract In the past few years, many digital twin models have been developed for assembly accuracy prediction and parameter optimization of complex products. Considering further research and application, some key technologies should not be ignored. For example, digital twin models for assembly should be enhanced to fulfill varying requirements. Fidelity of digital twin models should be evaluated to support decision making. Uncertainty of digital twin models should also be investigated to improve reliability of prediction and optimization. This presentation aims to offer an insight into these key technologies for reference.

Abstract Due to the fully enclosed or semi-enclosed characteristics of aircraft component docking areas, the assembly process is often challenged by limited visibility and measurability, making it difficult to accurately adjust component poses and ensure assembly quality. The report explores simulation and quality monitoring technologies for aircraft component docking assembly based on digital twin model. Firstly, the docking process and gap uniformity are modeled, and then a digital twin model of the mating components is established using geometric state data acquired through line-laser scanning. Subsequently, inspired by the concept of virtual-driven real-world control, a digital twin-driven precision assembly adjustment algorithm is proposed, which integrates virtual and physical systems through progressive alignment and iterative trial assembly. Finally, a test platform for large fuselage barrels is established. Through a series of docking experiments, the effectiveness and feasibility of the proposed digital twin simulation framework and precision assembly adjustment algorithm are validated.