Due to small production volume in aircraft industry, the available information of variation sources is often not enough to make assumptions on their probabilistic characteristics, especially in the stage of prototype manufacturing. To deal with the problem, an assembly variation modeling and analysis method based on the elasticity mechanics and interval approach is proposed for aircraft assembly. First, variation sources are modeled as bounded convex sets, which are defined as interval structural parameters in interval arithmetic. Then, variation modeling and analysis are successively implemented using the method of influence coefficient and interval arithmetic. After that, a uniform-splitting method is applied to achieve the refinement of the interval extension in variation analysis. To reduce the complexity of the finite element analysis and assembly variation computation, part deformation forms including warpage and torsion are concisely characterized with angle instead of the deviations of isolated key points on the part. The comparison of the assembly variations estimated with the proposed variation analysis method and actual experiment results verifies the effectiveness of the constructed assembly variation model and the proposed method. The interval approach–based assembly variation analysis method is a good complement to traditional probabilistic approach–based methods for compliant assembly systems, which is suited for linear and linearized nonlinear assembly systems. The proposed method provides an improved understanding of the application of compliant assembly variation analysis methods in aircraft manufacturing.

Purpose: – This paper aims to propose a roadmap to control the robot–subassembly (R–S) coordination errors in movable robotic drilling. Fastener hole drilling for multi-station aircraft assembly demands a robotic drilling system with expanded working volume and high positioning accuracy. However, coordination errors often exist between the robot and the subassembly to be drilled because of disturbances. Design/methodology/approach: – Mechanical pre-locating and vision-based robot base frame calibration are consecutively implemented to achieve in-process robot relocation after station transfer. Thus, coordination errors induced by robotic platform movements, inconsistent thermal effects, etc. are eliminated. The two-dimensional (2D) vision system is applied to measure the remainder of the R–S coordination errors, which is used to enhance the positioning accuracy of the robot. Accurate estimation of measured positioning errors is of great significance for evaluating the positioning accuracy. For well estimation of the positioning errors with small samples, a bootstrap approach is put forward. Findings: – A roadmap for R–S coordination error control using a 2D vision system, composed of in-process relocation, coordination error measurement and drilled position correction, is developed for the movable robotic drilling. Practical implications: – The proposed roadmap has been integrated into a drilling system for the assembly of flight control surfaces of a transport aircraft in Aviation Industry Corporation of China. The position accuracy of the drilled fastener holes is well ensured. Originality/value: – A complete roadmap for controlling coordination errors and improving positioning accuracy is proposed, which makes the high accuracy and efficiency available in movable robotic drilling for aircraft manufacturing.