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Aircraft assembly demands high position accuracy of drilled fastener holes. Automated drilling is a key technology to fulfill the requirement. The purpose of the paper is to conduct positioning variation analysis and control for an automated drilling to achieve a high positioning accuracy.

The nominal and varied connective models of automated drilling are constructed for positioning variation analysis regarding automated drilling. The principle of a strategy for reducing positioning variation in drilling, which shortens the positioning variation chain with the aid of an industrial camera-based vision system, is explored. Moreover, other strategies for positioning variation control are developed based on mathematical analysis to further reduce the position errors of the drilled fastener holes.

The propagation and accumulation of an automated drilling system’s positioning variation are explored. The principle of reducing positioning variation in an automated drilling using a monocular vision system is discussed from the view of variation chain.

The strategies for reducing positioning variation, rooted in the constructed positioning variation models, have been applied to a machine-tool based automated drilling system. The system is developed for a wing assembly of an aircraft in the Aviation Industry Corporation of China.

Propagation, accumulation and control of positioning variation in an automated drilling are comprehensively explored. Based on this, the positioning accuracy in an automated drilling is controlled below 0.13 mm, which can meet the requirement for the assembly of the aircraft.

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 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.

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.

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.

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.

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.

Assembly variations, which will propagate along the assembly process, are inevitable and difficult to analyze in Aeronautical Thin‐Walled Structures (ATWS) assembly. The purpose of this paper is to present a new method for analyzing the variation propagation of ATWS with automated riveting.

The paper addresses the variation propagation model and method by first, forming a novel Stage‐State model to represent the process of automated riveting. Second, the effect of positioning error on assembly variation is defined as propagation variation (PV), and propagation matrix of key characteristic points (KCP) is discussed. Third, the effect between the variations in each stage is defined as expansion variation (EV). According to the analysis of mismatch error and the reference transformation, the expansion matrix is formed.

The model can solve the variation propagation problem of ATWS with automated riveting efficiently, which is shown as an example of this paper.

The variation obtained by the model and method presented in this paper is in conformity with the variation measured in experiments.

The propagation variation and expansion variation is proposed for the first time, and variations are studied according to novel propagation matrix and expansion matrix.

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.

Component positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.

First, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.

During the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.

In this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

As Chinese massage is increasingly popular, many physicians are needed these days. In order to promote the experience and skills of experts and reduce labour intensity during massage, a massage robot, which could reproduce the expert techniques with individualized manipulation parameters and enhanced safety control strategies, is presented in this paper.

The kinematic and force features of key massage techniques, such as Thumb Kneading, Pressing, Rolling, Vibrating and Pinching, are summarized by analyzing the massage processes of expert physicians, and a mathematical model for robotic massage is established. With safety issues taken into account, the overall system structure of the massage robot is proposed. The system generally consists of a positioning platform and a massage end‐effector which implements the massage techniques, and the end‐effector is further divided into a parallel mechanism and a massage hand to accommodate different techniques. Visual tracking is used for positioning acupuncture points by recognizing markers on a massage vest worn by the patient. A pain threshold value is introduced to individualize therapy schemes and a force‐position control method based on the pain threshold is presented.

VAS (Visual Analogue Scale) tests for lumbar muscle strain are carried out using the massage robot, and the treatment effect of the massage robot based on traditional Chinese massage therapy theory is initially validated.

The treatment effect of the massage robot needs to be assessed clinically for more occasions and more clinical experiments will be conducted, to optimize the configuration and control strategy to meet the clinical needs in future work.

The robotic massage system presented in this paper is acting on acupuncture points based on traditional Chinese massage therapy theory, with human manipulation techniques reproduced and expert experiences incorporated. The massage robot can take the place of a massager to perform Chinese massage. Most of the massage robotic systems published in the world perform only one massage technique and the whole massage process is not completely considered. By comparison, the authors' massage robot could perform five techniques. Furthermore, the authors have designed the procedure of robotic massage specifically for patients who suffer from lumbar muscle strain.

The purpose of this paper is to provide a conceptual framework which connects theory with straightforward application of statistical process control (SPC) in discovering and analyzing causes of variation to eliminate quality problems, which not only helps small and medium enterprises (SMEs) to improve their processes but also helps to attain competitive positioning.

Based on theory and methodological framework, an experimental study has been presented. Use of histograms, X (bar) and R control charts and process capability plots and cause-and-effect diagrams have been made to analyse the assignable causes. A case from an SME engaged in machining of automotive parts is investigated.

The results demonstrate the effectiveness of SPC in evaluating and eliminating quality problems. The machine capability (C_P) and the process capability (C_Pk) values are also obtained to know inherent variation in the process. If these quality tools are applied with management support and apt knowledge, attained through proper training and motivation, then in this cut-throat competitive world, SMEs can establish their market position by enhancing the quality and productivity of their products/processes.

From the study, the authors conclude that application of SPC requires thorough preparation, management commitment and human resource management through proper training, teamwork and motivation embedded with a sound measurement and control system.

The present study bridges the gap between theory and practice by developing a conceptual framework and providing a practical support by illustrating a case from an SME engaged in machining of automotive parts.

A simplified global positioning system (GPS) error model including models for a variety of abnormal operational conditions and failures is developed to provide simulation tools for the design, testing, and evaluation of autonomous flight fault tolerant control laws. The paper aims to discuss these issues.

Analysis and experimental data are used to build simplified models for GPS position and velocity errors on all three channels. The GPS model is interfaced with West Virginia University unmanned aerial vehicles (UAV) simulation environment and its utility demonstrated through simulation for several autonomous flight scenarios including GPS abnormal operation.

The proposed simplified GPS model achieves desirable levels of accuracy and realism for all components for the purpose of general UAV dynamic simulation and development of fault tolerant autonomous flight control laws.

The simplified GPS model allows investigating GPS malfunction effects on the performance of autonomous UAVs and designing trajectory tracking algorithms with advanced fault tolerant capabilities.

The simplified GPS model has proved to be a flexible and useful tool for UAV simulation and design of autonomous flight control laws at normal and abnormal conditions.

The outcomes of this research effort achieve a level of detail never attempted before in modeling GPS operation at normal and abnormal conditions for UAV simulation and autonomous flight control laws design using a simplified framework.