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The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

Virtual voxels (3D pixels) have traditionally been used as a graphical data structure for representing 3D geometry. The purpose of this paper is to study the use of pre‐existing physical voxels as a material building‐block for layered manufacturing and present the theoretical underpinnings for a fundamentally new massively parallel additive fabrication process in which 3D matter is digital. The paper also seeks to explore the unique possibilities enabled by this paradigm.

Digital RP is a process whereby a physical 3D object is made of many digital units (voxels) arranged selectively in a 3D lattice, as opposed to analog (continuous) material commonly used in conventional rapid prototyping. The paper draws from fundamentals of 3D space‐filling shapes, large‐scale numerical simulation, and a survey of modern technology to reach conclusions on the feasibility of a fabricator for digital matter.

Design criteria and appropriate 3D voxel geometries are presented that self‐align and are suitable for rapid parallel assembly and economical manufacturing. Theory and numerical simulation predict dimensional accuracy to scale favorably as the number of voxels increases. Current technology will enable rapid parallel assembly of billions of microscale voxels.

Many novel voxel functions could be realized in the electromechanical and microfluidic domains, enabling inexpensive prototyping of complex 3D integrated systems. The paper demonstrates the feasibility of a 3D digital fabricator, but an instantiation is out of scope and left to future work.

Digital manufacturing offers the possibility of desktop fabrication of perfectly repeatable, precise, multi‐material objects with microscale accuracy.

The paper constitutes a comprehensive review of physical voxel‐based manufacturing and presents the groundwork for an emerging new field of additive manufacturing.

The purpose of this paper is to propose an assembly coordination modelling approach based on measured data for assembly quality control of multi-constrained objects in aircraft assembly. This approach aims to establish a high-precision digital mirror of physical assembly system in the virtual environment, with which the assembly process in the virtual environment can be performed synchronously with that in the physical world.

This paper presents a realistic geometrical representation model based on measured point cloud, as well as the multiple constraints modelling methods for local and global constraints with the proposed representation model. For the assembly target optimization, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, where the particle swarm optimization and simulated annealing algorithm are combined to calculate the optimal solutions.

As shown in the validation results, the minimum easiness value for easiness model in global optimization is 3.01, while the best value for weighting model by adjusting weights for more than 10 times is 1.94. The results verify that the proposed coordination modelling approach is effective to the assembly of multi-constrained objects, and the optimization model has an obvious advantage over the traditional weighting method.

This paper provides a new idea for the fine control of assembly quality of non-ideal components by introducing the measured data into the on-line assembly process. Besides, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, which overcomes the problem of traditional weighting model wherein the weightings are difficult to determine.

The purpose of this paper is to design a new method to realize automatic assembly of aircraft components with large shafts such as canard and vertical tail. The assembly structure of component with large shaft and fuselage is a mating assembly structure, and it is a challenge to satisfy the precision and assembly requirement.

According to the assembly structure features and process requirements of an aircraft component with large shaft, the operating principle of precise assembly system for shaft-hole mating is analyzed in this paper. The model of compliant assembly for shaft-hole mating is constructed, and force condition analysis of the compliant assembly is performed. An automatic precise shaft-hole assembly method for aircraft assembly using 5 degrees of freedom spatial mechanism, compliance technology and servo feeding system is put forward based on the analysis. A 5 degrees of freedom passive compliant experimental equipment has been developed.

Application test results of the 5 degrees of freedom passive compliant experimental equipment show that the simulated canard can be mated automatically and accurately through this method with high efficiency and high quality as long as the tip of shaft enters into the range of hole’s chamfer.

This method has been used in an aircraft assembly project. The practical results show that the aircraft components with large shafts can be mated automatically and accurately through this method with high efficiency and high quality.

This paper presents a new method and designs a new assembly system to realize the assembly of the aircraft components with large shafts. The research will promote the automation of fuselage assembly.

In aircraft wing–fuselage assembly, the distributed multi-point support layout of positioners causes fuselage to deform under gravity load, leading to assembly difficulty and assembly stress. This paper aims to propose a hybrid force position control method to balance aerodynamic shape accuracy and deformation of assembly area, thereby correcting assembly deformation and reducing assembly stress.

Force and position control axes of positioners are selected based on screw theory and ellipsoid method. The position-control axes follow the posture trajectory to align the fuselage posture. To exert force on the fuselage and correct the deformations, the force-control axes follow the contact force derived by using orthogonal experiments and partial least squares regression (PLSR). Finite element simulation and one-dimension deformation correction experiment are conducted to verify the validity of this method.

Simulation results indicate that hybrid force position control method can correct assembly deformation and improve the wing–fuselage assembly quality significantly. Experiment on specimen verifies the effect of this method indirectly.

The proposed method gives a solution to solve the deformation problem during aircraft wing-fuselage assembly, thereby reducing assembly stress and improving assembly quality.

The purpose of this paper is to investigate the nonlinear dynamics of the aircraft assembly lines. An approach for modeling and analyzing the production rate of an aircraft assembly line is introduced using the chaos theory.

First, two key system variables including reliability and learning ability are considered to control the dynamics model. The discrete-time dynamics equation of the production rate is established as a function of the reliability and the learning rate. Then an improved Gauss-learning curve is proposed and applied to aircraft assembling condition. Finally, the bifurcation diagrams and the maximal Lyapunov exponents are used and applied to the experimental study to analyze the dynamic behavior under different combinations of parameters.

On the basis of the experimental study, it is shown that chaotic behavior really exists in the aircraft assembly lines. The reliability and the Gauss-learning curve can nonlinearly affect the production rate.

This paper applied nonlinear dynamics and chaotic theory to the production analyses of the aircraft assembly lines for the first time. The proposed model has been successfully applied to a practical case, and the result justifies its advantage as well as feasibility to both theory and engineering application.

The purpose of this paper is to propose a posture evaluation approach based on temperature compensation and three-dimensional (3-D) tolerance for the key points (KPs).

A large component 3-D compensation model of thermal deformation considering characteristics of the assembly object is developed. Then, the thermal deformation compensation model is used to modify the nominal coordinates for the KPs. By using a combination of relative deviations of KPs as the objective and 3-D tolerance as the constraints, an optimization model for posture evaluation is established.

Deviations of posture and KPs’ coordinates are obtained by solving the non-linear constrained optimization problem. The posture evaluation method is demonstrated in both a simulation case and practical implication of the aircraft components assembly system with the result that a good performance is obtained.

The proposed method has been used in several aircraft assembly projects in China, and gained a good effect.

This paper proposes a method for eliminating the affection of thermal deformation during posture evaluation process and improving the consistency and stability of posture evaluation results. The results of this research will help to systematically improve the manufacturing process and tolerance allocation efficiency in large aircraft assembly.

This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.

This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.

In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.

In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.

The aim of this paper is to present a new variation modeling method for fuselage structures in digital large aircraft assembly. The variation accumulated in a large aircraft assembly process will influence the dimensional accuracy and fatigue life of airframes. However, in digital large aircraft assembly, variation analysis and modeling are still unresolved issues.

An elastic structure model based on beam elements is developed, which is an equivalent idealization of the actual complex structure. The stiffness matrix of the structure model is obtained by summing the stiffness matrices of the beam elements. For each typical stage of the aircraft digital assembly process, including positioning, coordinating, joining and releasing, variation models are built using the simplified structure model with respective loads and boundary conditions.

Using position errors and manufacturing errors as inputs, the variations for every stage of the assembly process can be calculated using the proposed model.

This method has been used in a large fuselage section assembly project, and the calculated results were shown to be a good prediction of variation in the actual assembly.

Although certain assumptions have been imposed, the proposed method provides a better understanding of the assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.

This paper aims to promote the integration of the relative position accuracy (RPA) measurement and evaluation in digital assembly process by adopting the model-based method. An integrated framework for RPA measurement is proposed based on a model-based definition (MBD) data set. The study also aims to promote the efficiency of inspection planning of RPA measurement by improving the reusability and configurability of the inspection planning.

The works have been carried out on three layers. In the data layer, an extended MBD data set is constructed to describe the objects and data for defining RPA measurement items; In definition layer, a model based and hierarchical structure for RPA item definition is constructed to support quick definition for RPA measurement items. In function layer, a toolset consisting three modules is constructed in a sequence from measurement planning to RPA value solving to visualized displaying again. Based on this framework, a prototype system is developed.

The paper provides an identified practice of model-based inspection. It suggests that MBD is valuable in promoting both the integration and efficiency of digital inspection.

The templates and constructed geometry objects given in this paper are still limited in a scenario of aircraft assembly. The integrity and universality of them still need follow-up works.

The paper includes implications for the model based digital inspection, the digital assembly and the extended application of MBD.

This paper expands the application of MBD in inspection and fulfils the need to promote the integration and efficiency of digital inspection in large-scale component assembly.