Jiangxiong Li

The accuracy of industrial robots is critical in many manufacturing applications. In this case, a self-developed automated fiber placement heavy-duty robot is used for the lay-up of carbon fiber composite prepregs, which requires high positioning accuracy. The mass of the robot body and end-effector exceeds 3 tons and 1 ton, respectively, resulting in considerable deformation and other errors due to the huge size and mass. Paradoxically, the work that our robot engaged in requires high precision, and the positioning accuracy needs to be less than 0.5 mm. This paper conducts a comprehensive analysis of the robot joint error, so as to improve the accuracy of the robot. A torsional and capsize deformation model for joints is established. In addition, the capsize torque and capsize axis of joint deformation are derived to determine the transformation relationship between joint frames. Chebyshev polynomials are used to describe joint-dependent errors. The Levenberg–Marquarelt (L–M) algorithm was used to identify the error model parameters. The effects of different error factors on the positioning accuracy were compared and analyzed. The validation result shows that the proposed model describes 88.11% of the positioning error, and the average residual error of the calibration can reach 0.132 mm. The identified joint-dependent error and the compliance error are 0.296 mm and 0.240 mm, accounting for 26.67% and 21.62% of the positioning error, respectively.

The slug rivet installation process is complex. A lot of parameters are included during the riveting deformation process. The workload and time cost of a traditional simulation study is very high since a traditional numerical model should be modified manually time by time when riveting parameters change. The data processing after simulation is another complex work. To improve the situation, this paper presents a parameterized modeling method. The modeling process and data processing algorithm can be developed using Python script. The parameterized model can automatically and continuously re-build without any manual intervention according to the riveting parameter auto-update condition. The post-processing analysis can be automatically conducted and saved as well. Then this paper conducts continuous analysis to illustrate the impact of riveting parameters on riveting quality. The parameterized model keeps running 41 times until the riveting parameter is out of range. The parameterized modeling method is a useful method for a simulation study. The study will pave the way for further investigations.

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Practical implications: 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. Originality/value: 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.

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Practical implications: This method has been tested with simulated model data and real product data, the results of which have shown efficient coordination of mating components. Originality/value: 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.

In aircraft assembly, multiple laser trackers are used simultaneously to measure large-scale aircraft components. To combine the independent measurements, the transformation matrices between the laser trackers’ coordinate systems and the assembly coordinate system are calculated, by measuring the enhanced referring system (ERS) points. This article aims to understand the influence of the configuration of the ERS points that affect the transformation matrix errors, and then optimize the deployment of the ERS points to reduce the transformation matrix errors. To optimize the deployment of the ERS points, an explicit model is derived to estimate the transformation matrix errors. The estimation model is verified by the experiment implemented in the factory floor. Based on the proposed model, a group of sensitivity coefficients are derived to evaluate the quality of the configuration of the ERS points, and then several typical configurations of the ERS points are analyzed in detail with the sensitivity coefficients. Finally general guidance is established to instruct the deployment of the ERS points in the aspects of the layout, the volume size and the number of the ERS points, as well as the position and orientation of the assembly coordinate system.