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This paper develops the statistical error analysis model for assembling, to derive measures of controlling the geometric variations in assembly with multiple assembly stations, and to provide a statistical tolerance prediction/distribution toolkit integrated with CAD system for responding quickly to market opportunities with reduced manufacturing costs and improved quality. First the homogeneous transformation is used to describe the location and orientation of assembly features, parts and other related surfaces. The desired location and orientation, and the related fixturing configuration (including locator position and orientation) are automatically extracted from CAD models. The location and orientation errors are represented with differential transformations. The statistical error prediction model is formulated and the related algorithms integrated with the CAD system so that the complex geometric information can be directly accessed. In the prediction model, the manufacturing process (joining) error, induced by heat deformation in welding, is taken into account.

Manufacturing errors, which will propagate along the assembly process, are inevitable and difficult to analyze for complex products, such as aircraft. To realize the goal of precise assembly for an aircraft, with revealing the nonlinear transfer mechanism of assembly error, a set of analytical methods with response to the assembly error propagation process are developed. The purpose of this study is to solve the error problems by modeling and constructing the coordination dimension chain to control the consistency of accumulated assembly errors for different assemblies.

First, with the modeling of basic error sources, mutual interaction relationship of matting error and deformation error is analyzed, and influence matrix is formed. Second, by defining coordination datum transformation process, practical establishing error of assembly coordinate system is studied, and the position of assembly features is modified with actual relocation error considering datum changing. Third, considering the progressive assembly process, error propagation for a single assembly station and multi assembly stations is precisely modeled to gain coordination error chain for different assemblies, and the final coordination error is optimized by controlling the direction and value of accumulated error range.

Based on the proposed methodology, coordination error chain, which has a direct influence on the property of stealthy and reliability for modern aircrafts, is successfully constructed for the assembly work of the jointing between leading edge flap component and wing component at different assembly stations.

Precise assembly work at different assembly stations is completed to verify methodology’s feasibility. With analyzing the main comprised error items and some optimized solutions, benefit results for the practical engineering application showing that the maximum value of the practical flush of the profiles between the two components is only 0.681 mm, the minimum value is only 0.021 mm, and the average flush of the entire wing component is 0.358 mm, which are in accordance with theoretical calculation results and can successfully fit the assembly requirement. The potential user can be the engineers for manufacturing the complex products.

The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.

Event trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.

This paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.

While the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.

Production managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.

This is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.

The purpose of this study is to establish an assembly accuracy analysis model of deployable arms based on Jacobian–Torsor theory to improve the assembly accuracy. Spacecraft deployable arm is one of the core components of spacecraft. Reducing the errors in assembly process is the main method to improve the assembly accuracy of spacecraft deployable arms.

First, the influence of composite connecting rod, root joint and arm joint on assembly accuracy in the tandem assembly process is analyzed to propose the assembly accuracy analysis model. Second, a non-tandem assembly process of “two joints fixed-composite rod installed-flange gasket compensated” is proposed and analyzed to improve the assembly accuracy of deployable arms. Finally, the feasibility of non-tandem assembly process strategy is verified by assembly experiment.

The experiential results show that the assembly errors are reduced compared with the tandem assembly process. The errors on axes x, y and z directions decreased from 14.1009 mm, 14.2424 mm and 0.8414 mm to 0.922 mm, 0.671 mm and 0.2393 mm, respectively. The errors round axes x and y directions also decreased from 0.0050° and 0.0053° to 0.00292° and 0.00251°, respectively.

This paper presents an assembly accuracy analysis model of deployable arms and applies the model to calculate assembly errors in tandem assembly process. In addition, a non-tandem assembly process is proposed based on the model. The experimental results show that the non-tandem assembly process can improve the assembly accuracy of deployable arms.

Assembly errors of aeroengine rotor must be controlled to improve the aeroengine efficiency. However, current method cannot truly reflect assembly errors of the rotor in working state owing to difficulties in error analysis. Therefore, the purpose of this study is to establish an optimization method for aeroengine rotor stacking assembly.

The assembly structure of aeroengine rotor is featured. Rotor eccentricity is optimized based on Jacobian–Torsor model. Then, an optimization method for assembly work is proposed. The assembly process of the high-pressure compressor rotor and the high-pressure turbine rotor as the rotor core assembly is mainly considered.

An aeroengine rotor is assembled to verify the method. The results show that the predicted eccentricity differed from the measured eccentricity by 6.1%, with a comprehensive error of 8.1%. Thus, the optimization method has certain significance for rotor assembly error analysis and assembly process optimization.

In view of the error analysis in the stacking assembly of aeroengine rotor, an innovative optimization method is proposed. The method provides a novel approach for the aeroengine rotor assembly optimization and is applicable for the assembly of high-pressure compressor rotor and high-pressure turbine rotor as the rotor core assembly.

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.

The purpose of this paper is to propose an on-line iterative compensation method combining with a feed-forward compensation method to enhance the assembly accuracy of a metrology-integrated robot system (MIRS).

By the integration of a six degrees of freedom (6DoF) measurement system (T-Mac), the robot’ movement can be tracked with real-time measurement. With the on-line measured data, the proposed iterative compensation for absolute positioning and the feed-forward compensation for relative linear motion are integrated into the assembly process to improve the assembly accuracy.

It is found that the MIRS exhibits good performance in both accuracy and efficiency with the application of the proposed compensation method. With the proposed assembly process, a component can be automatically aligned to the target in seconds, and the assembly error can be decreased to 0.021 mm for position and 0.008° for orientation on average.

This paper presents a 6DoF MIRS for high-precision assembly. Based on the system, a novel on-line compensation method is proposed to enhance the assembly accuracy. In this paper, the assembly accuracy and the corresponding distance parameter are given by a series of experiments as reference for assembly applications.

The coupling impact of hybrid uncertain errors on the machine precision is complex, as a result of which the designing method with multiple independent error sources under uncertainties remains a challenge. For the purpose of precision improvement, this paper focuses on the robot design and aims to present an assembly precision design method based on uncertain hybrid tolerance allocation (UHTA), to improve the positioning precision of the mechanized robot, as well as realize high precision positioning within the workspace.

The fundamentals of the parallel mechanism are introduced first to implement concept design of a 3-R(4S) &3-SS parallel robot. The kinematic modeling of the robot is carried out, and the performance indexes of the robot are calculated via Jacobian matrix, on the basis of which, the 3D spatial overall workspace can be quantified and visualized, under the constraints of limited rod, to avoid the singular position. The error of the robot is described, and a probabilistic error model is hereby developed to classify the hybrid error sensitivity of each independent uncertain error source by Monte Carlo stochastic method. Most innovatively, a methodology called UHTA is proposed to optimize the robot precision, and the tolerance allocation approach is conducted to reduce the overall error amplitude and improve the robotized positioning precision, on the premise of not increasing assembly cost.

The proposed approach is validated by digital simulation of medical puncture robot. The experiment highlights the mathematical findings that the horizontal plane positioning error of the parallel robotic mechanism can be effectively reduced after using UHTA, and the average precision can be improved by up to 39.54%.

The originality lies in UHTA-based precision design method for parallel robots. The proposed method has widely expanding application scenarios in industrial robots, biomedical robots and other assembly automation fields.

The modern manufacturing industry has put forward higher requirements for the assembly accuracy of components with the development of the industrial technology. For precision assembly, the traditional assembly process study based on tolerance has had difficulty in meeting these requirements. Hence, the distribution of the form errors must be considered. The registration between the two mating surfaces with form errors determines the parts’ assembly position, and is the basis for the prediction and control of the assembly accuracy. This study aims to provide a new surfaces registration method which takes form errors into consideration.

This study presents a new registration approach based on the minimum potential energy. A unique set of contact points on mating surfaces that meet the actual conditions can be obtained and the spatial position of the assembled part is calculated.

The experimental results show that the calculated values are in good agreement with the experimental values. Furthermore, the root mean square error is within 2%, which proves the validity and accuracy of the approach.

This paper provides an effective and new method for precision assembly which takes form errors into consideration. The method can give the optimal solution of the contact points, which is more consistent with the actual assembly situation and provides a basis for predicting assembly accuracy.

The purpose of this paper is to study the effect of the gamification of virtual assembly planning on the user performance, user experience and engagement.

A multi-touch table was used to manipulate virtual parts and gamification features were integrated into the virtual assembly environment. An experiment was conducted in two conditions: a gamified and a non-gamified virtual environment. Subjects had to assemble a virtual pump. The user performance was evaluated in terms of the number of errors, the feasibility of the generated assembly sequence and the user feedback.

The gamification reduced the number of errors and increased the score representing the number of right decisions. The results of the subjective and objective analysis showed that the number of errors decreased with engagement in the gamified assembly. The increase in the overall user experience reduced the number of errors. The subjective evaluation showed a significant difference between the gamified and the non-gamified assembly in terms of the level of engagement, the learning usability and the overall experience.

The effective learning retention after training has not been tested, and longitudinal studies are necessary. The effect of the used gamification elements has been evaluated as a whole; further work could isolate the most beneficial features and add other elements that might be more beneficial for learning.

The research reported in this paper provides valuable insights into the gamification of virtual assembly using a low-cost multi-touch interface. The results are promising for training operators to assemble a product at the design stage.