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In order to make the construction industry develop in the direction of greening, this paper analyzes whether the application of intelligent technology in prefabricated buildings can achieve carbon emission reduction, starting from the problems of weak technology and insufficient encouragement policies in the prefabricated building industry. It also designs dynamic and adjustable incentives for the smart transformation of prefabricated buildings and makes recommendations to facilitate the transformation of assembly manufacturers into “smart factories”.

This paper takes the intelligent technology for carbon reduction, energy efficiency and policy design in the prefabricated buildings industry as the starting point. Based on in-depth expert interviews and questionnaire survey data, a linear multiple regression model is used to establish an association network of intelligent technology in the production and transportation, construction, operation and maintenance, demolition and scrapping stages. On this basis, an evolutionary game theory is used to construct a smart transformation and carbon reduction utility game model between the government and manufacturers, and relevant suggestions for smart empowerment of green construction development technology combinations and policy settings are proposed.

An assembly manufacturing plant with smart empowerment is an important way to achieve green and sustainable development in the construction industry. Among them, BIM and IoT have made a greater impact on carbon emission reduction of prefabricated buildings in all stages of the whole life cycle. The government’s proposed energy efficiency incentives and environmental tax amount will effectively increase companies' motivation for smart transformation of prefabricated buildings. However, when the environmental tax amount is low, the government should strengthen the regulation of the industry in order to increase the speed of smart transformation of assembly manufacturers. Therefore, a reasonable setting of the environmental tax rate and energy-saving incentives and flexible adjustment of the regulatory efforts can maximize the functional utility of the government in the process of smart transformation.

This paper focuses on the impact of intelligent technologies on the overall carbon emissions of the industry and provides an evolutionary analysis of the strategic game between the government and assembly manufacturers, the main players in the smart transformation process of prefabricated buildings. However, smart technologies for different categories of assembly manufacturing plants and strategic options for a wider range of stakeholders have not been examined in depth.

Different from existing research, this study focuses on exploring the strategic game between the government and assembly manufacturers in the smart transformation of prefabricated buildings. It provides an innovative explanation of the connection between intelligent technology and carbon emissions. The study develops an evolutionary game model for both parties, addressing the research gap on the combined effects of policy incentives and intelligent technology on carbon reduction and efficiency improvement in the prefabricated buildings industry. This research not only offers practical reference for the government in designing incentive mechanisms and establishing regulatory systems but also provides feasible practical guidance for the smart transformation and carbon reduction efforts of assembly manufacturing plants.

The purpose of this paper is to introduce a robotic boring system for intersection holes in aircraft assembly. The system is designed to improve the boring quality and position accuracy of the intersection holes.

To improve the boring quality of intersection holes, a robot posture optimization model is established. The target of the model is to maximize the robot stiffness and the variate is location of the robot on the guideway. The model is solved by the iterative IKP algorithm based on the Jacobian matrix. To improve the position accuracy of intersection holes, a robot positioning accuracy compensation method is introduced. In the method, a laser tracker is used to measure the actual position and orientation of the boring bar. Combined with the desired position and orientation, the error can be obtained and compensated.

In practical case of the robotic boring system, the robot stiffness is effectively improved and the surface roughness of intersection holes achieves a grade of Ra0.8. Besides, the robot end achieves a position accuracy of 0.05 mm and an orientation accuracy of 0.05°.

The robotic boring system has been applied successfully in one of the aircraft assembly projects in northwest China.

The robotic boring system can be applied for machining intersection holes in an aircraft assembly. With the robot posture optimization method and accuracy compensation method, the boring quality and position accuracy of the intersection holes can be guaranteed.

This paper aims to improve the alignment accuracy of large components in aircraft assembly and an evaluation algorithm, which is based on manufacture accuracy and coordination accuracy, is proposed.

With relative deviations of manufacturing feature points and coordinate feature points, an evaluation function of assembly error is constructed. Then the optimization model of large aircraft digital alignment is established to minimize the synthesis assembly error with tolerance requirements, which consist of three-dimensional (3D) tolerance of manufacturing feature points and relative tolerance between coordination feature points. The non-linear constrained optimization problem is solved by Lagrange multiplier method and quasi-Newton method with its initial value provided by the singular value decomposition method.

The optimized postures of large components are obtained, which makes the tolerance of both manufacturing and coordination requirements be met. Concurrently, the synthesis assembly error is minimized. Compared to the result of the singular value decomposition method, the algorithm is validated in three typical cases with practical data.

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

This paper proposes a method to optimize the manufacturing and coordination accuracy with tolerance constraints when the postures of several components are adjusted at the same time. The results of this paper will help to improve the quality of component assemblies.

This paper aims to present a modeling and analysis approach for multi-station aircraft assembly to predict assembly variation. The variation accumulated in the assembly process will influence the dimensional accuracy and fatigue life of airframes. However, in digital large aircraft assembly, variation propagation analysis and modeling are still unresolved issues.

Based on an elastic structure model and variation model of multistage assembly in one station, the propagation of key characteristics, assembly reference and measurement errors are introduced. Moreover, the reposition and posture coordination are considered as major aspects. The reposition of assembly objects in a different assembly station is described using transformation and blocking of coefficient matrix in finite element equation. The posture coordination of the objects is described using homogeneous matrix multiplication. Then, the variation propagation model and analysis of large aircraft assembly are established using a discrete system diagram.

This modeling and analysis approach for multi-station aircraft assembly reveals the basic rule of variation propagation between adjacent assembly stations and can be used to predict assembly variation or potential dimension problems at a preliminary assembly phase.

The modeling and analysis approaches have been used in a transport aircraft project, and the calculated results were shown to be a good prediction of variation in the actual assembly.

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

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

This paper aims to provide a shimming method based on scanned data and finite element analysis (FEA) for a wing box assembly involving non-uniform gaps. The effort of the present work is to deal with gap compensation problem using hybrid shims composed of solid and liquid forms.

First, the assembly gaps of the mating components are calculated based on the scanned surfaces. The local gap region is extracted by the seed point and region growth algorithm from the scattered point cloud. Second, with the constraints of hole margin, gap space and shim specification, the optional shimming schemes are designed by the exhaustive searching method. Finally, the three-dimensional model of the real component is reconstructed based on the reverse engineering techniques, such as section lines and sweeping. Using FEA software ABAQUS, the stress distribution and damage status of the joints under tensile load are obtained for optimal scheme selection.

With the scanned mating surfaces, the non-uniform gaps are digitally evaluated with accurate measurement and good visualization. By filling the hybrid shims in the assembly gaps, the joint structures possess similar load capacity but stronger initial stiffness compared to the custom-shimmed structures.

This method has been tested with the interface data of a wing tip, and the results have shown good efficiency and automation of the shimming process.

The proposed method can decrease the manufacturing cost of shims, shorten the shimming process cycle and improve the assembly efficiency.

The purpose of this paper is to present an optimal posture evaluation model to control the assembly gaps in aircraft wing assembly. The gaps between two mating surfaces should be strictly controlled in precision manufacturing. Oversizing of gaps will decrease the dimensional accuracy and may reduce the fatigue life of a mechanical product. To reduce the gaps and keep them within tolerance, the relative posture (orientation and position) of two components should be optimized in the assembly process.

Based on the step alignment strategy, i.e. preliminary alignment and refined alignment, the concept of a small posture transformation (SPT) is introduced. In the preliminary alignment, an initial posture is estimated by a set of auxiliary locating points, with which the components can be quickly aligned near each other. In the refined alignment, the assembly gaps are calculated and the formulation of the gaps with component posture is derived by the SPT. A comprehensive weighted minimization model with gap tolerance constraints is established for redistributing the gaps in multi-regions. Powell-Hestenes-Rockafellar optimization, Singular Value Decomposition and K-Dimensional tree searching are introduced for the solution of the optimal posture for localization.

Using the SPT, the trigonometric posture transformation is linearized, which benefits the iterative solution process. Through the constrained model, overall gaps are minimized and excess gaps are controlled within tolerance.

This method has been tested with simulated model data and real product data, the results of which have shown efficient coordination of mating components.

This paper proposed an optimal posture evaluation method for minimizing the gaps between mating surfaces through component adjustments. This will promote the assembly automation and variation control in aircraft wing assembly.

Assembly variation analysis generally demands probability distributions of variation sources. However, due to small production volume in aircraft manufacturing, especially prototype manufacturing, the probability distributions are hard to obtain, and only the small-sample data of variation sources can be consulted. Thus, this paper aims to propose a variation analysis method driven by small-sample data for compliant aero-structure assembly.

First, a hybrid assembly variation model, integrating rigid effects with flexibility, is constructed based on the homogeneous transformation and elasticity mechanics. Then, the bootstrap approach is introduced to estimate a variation source based on small-sample data. The influences of bootstrap parameters on the estimation accuracy are analyzed to select suitable parameters for acceptable estimation performance. Finally, the process of assembly variation analysis driven by small-sample data is demonstrated.

A variation analysis method driven by small-sample data, considering both rigid effects and flexibility, is proposed for aero-structure assembly. The method provides a good complement to traditional variation analysis methods based on probability distributions of variation sources.

With the proposed method, even if probability distribution information of variation sources cannot be obtained, accurate estimation of the assembly variation could be achieved. The method is well suited for aircraft assembly, especially in the stage of prototype manufacturing.

A variation analysis method driven by small-sample data is proposed for aero-structure assembly, which can be extended to deal with other similar applications.

The riveting process is a metal forming process involving complex elastic-plastic deformation, which will induce a compressive residual stress field and cause local distortions in the connecting areas. Regarding to the aircraft panel assemblies with plenty of rivets, the global deformation is inevitable and undesired, leading difficulties to downstream assembly processes. This paper aims to present a new method for the local distortion calculation and the global deformation prediction of sheet panel assemblies during the automated riveting process.

In this paper, a simplified algebraic study is presented to analyze the local distortion of single countersunk rivet joint with the consideration of the barrel-like shape of the driven head and the through-thickness variations along the rivet shank. Then, an equivalent rivet unit is proposed based on the result of the algebraic study and embedded into the global-level model for the prediction of the overall distortions of riveted panels.

The algebraic study is able to reach a more precise contour of the deformed rivet than the traditional assumption of cylindrical deformations and rapidly determine the equivalent coefficients of the riveting unit. The result also shows an industrial acceptable accuracy of the prediction for the global deformations of the double-layered panel assemblies widely used in the aircraft panel structures.

A new local-global method for predicting the deformations of the riveted panel assembly based on the algebraic study of the local distortions is proposed to help the engineers in the early design stages or in the assembly process planning stage.

Wayfinding efficiency is an extremely influential factor to improve users' library interior experience. However, few research has studied the different functions of various wayfinding signages for university library users through mobile visual experiment. To fill this gap, the purpose of this paper is to explore the relationship between university library signage system design and patrons' wayfinding behavior features.

In this article, an eye movement tracking method was introduced to record eye movement data during the wayfinding process of participants in the library interior, targeting the cognition and psychology of library users in the wayfinding signage system. The visual guiding usability of landmarks, informational signages and directional signages were quantitatively tested, and the fixation on the signage system between orientation strategy users and route strategy users was compared. This study also investigated the effects of library users' spatial anxiety and environmental familiarity on their fixation on the area of interest of the wayfinding signage system using the differential test and regression.

This paper observed that informational signage had the best visual navigating competence. The difference of fixation duration and searching duration between patrons used various wayfinding strategies was significant. The informational signage was most attended by the route strategy users, and the orientation strategy users rarely focused on the directional signage. And participants with high anxiety tended to ignore the visually auxiliary function of the landmarks but paid attention to the directional signage. The participants with low anxiety could capture the landmarks that could not be easily found by the route strategy users. And participants less familiar with the environment were more sensitive to the landmarks. Furthermore, this paper offers optimization measures for university library wayfinding signage system, from the perspectives of informational signage understandability improvement, directional signage physical specification design and wayfinding assistant system with automatic landmark technology.

This article adds to the relatively sparse literature on university library user wayfinding experimental study in China. The experimental findings of this paper also have important practical implications for academic libraries' wayfinding system evaluation. The whole process could be seen as a repeatable and standard framework and methodology to inspect university library's wayfinding signage system usability and user wayfinding behavior performance.