A machining accuracy informed adaptive positioning method for finish machining of assembly interfaces of large-scale aircraft components

• Published in: Robotics and computer-integrated manufacturing Vol. 67; p. 102021
• Main Authors: Fan, Wei, Zheng, Lianyu, Ji, Wei, Xu, Xun, Lu, Yuqian, Wang, Lihui
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.02.2021; Elsevier BV
• Subjects: Accuracy; Adaptive positioning; Aircraft; Aircraft components; Algorithms; Assembly; Assembly interface; Engineering constraints; Function block; Interfaces; Large-scale aircraft component; Machining; Parameters; Particle swarm optimization; Passenger aircraft; Positioning devices (machinery); PSO-SA; Simulated annealing; Stabilizers (fluid dynamics); SVD; PCS; AP-CFB; LT; GLM; Adaptive positioning; Function block; SA; KC; MF; MP; IP; Assembly interface; PSO; MAC; OMM; ACS; MMP; CCS; PMP; PAC; PSO-SA; GCS; PF; ICP; Engineering constraints; Large-scale aircraft component; RMS; EPF; FB; MCS; LCS; LSOF; HLC
• ISSN: 0736-5845; 1879-2537; 1879-2537
• DOI: 10.1016/j.rcim.2020.102021

•An adaptive positioning method is proposed for large aircraft components to achieve high quality and efficiency positioning.•The definitions of PACs and MACs for the large component are given mathematically to support adaptive positioning.•An optimal pose evaluation model is put forward by fusing the PACs and MACs to calculate the optimal pose parameters. An assembly interface of a large-scale aircraft component is a joint surface to connect adjacent large components. To guarantee the final assembly accuracy of the large components, the assembly interface is finish machined on site before the final assembly to cut the observed machining allowance. Thus, aiming at realizing the high efficiency and high quality in the finish machining operation, in this paper we propose an adaptive positioning method that integrates comprehensive engineering constrains (including Positioning Accuracy Constraints (PACs) of the large component and Machining Accuracy Constraints (MACs) of the assembly interface). In this method, the key Measurement Points (MPs) of a component are assigned to obtain its initial pose. Then the measurement data and the initial pose are used as input data to obtain the optimal pose parameters of the component based on an improved Particle Swarm Optimization Simulated Annealing (PSO-SA) algorithm. The optimal pose parameters can provide data support for the adaptive positioning of the large component, the function of which is implemented based on IEC 61499 Function Block (FB) technology. Finally, a positioning experiment of a vertical tail of a large passenger aircraft is used to validate the proposed method. The experimental results illustrate that the proposed method can improve the efficiency and positioning accuracy of the large component, compared to the traditional method.