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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 propose an interpretation of the grey relational grade taking into account its variation range on the basis of the error propagation theory.

The paper uses error propagation theory to calculate the uncertainty of the grey relational grade, exploring how errors are propagated through the sequential operations of the grey relational analysis.

The non‐consideration of the error associated to the measurement of the experimental data that is transferred to the grey relational grade may have a potential effect on the interpretation of the grey relational rank. Data uncertainty quantification provides information about how well measurement fits to the value of the measured quantity and determines its validity. Therefore, this might lead one to consider that some sequences are less attractive than other lower‐ranked ones.

The combination of the grey and error propagation theories is a tool to choose the most accurate solution in grey relational grade ranks.

This study provides a new approach to interpret grey relational grade classifications.

This paper aims to propose a general and rigorous study on the propagation property of invariant errors for the model conversion of state estimation problems with discrete group affine systems.

The evolution and operation properties of error propagation model of discrete group affine physical systems are investigated in detail. The general expressions of the propagation properties are proposed together with the rigorous proof and analysis which provide a deeper insight and are beneficial to the control and estimation of discrete group affine systems.

The investigation on the state independency and log-linearity of invariant errors for discrete group affine systems are presented in this work, and it is pivotal for the convergence and stability of estimation and control of physical systems in engineering practice. The general expressions of the propagation properties are proposed together with the rigorous proof and analysis.

An example application to the attitude dynamics of a rigid body together with the attitude estimation problem is used to illustrate the theoretical results.

The mathematical proof and analysis of the state independency and log-linearity property are the unique and original contributions of this work.

The make‐or‐buy decision has been performed on the assumption that cost data are deterministic and accurate. The data available to decision makers are often highly imprecise because of estimation inaccuracy and/or errors in measurement. The bounded interval estimate is a common allowance scheme to compensate for the inherent estimating error. Applies the propagation of errors technique to evaluate make‐or‐buy alternatives with estimate errors. The numerical examples show how the proposed error analysis generates more discerning power when assessing competing alternatives.

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.

Many synchronization approaches are based on low-level time capturing, causing a tight integration with the Media Access Control (MAC) layer. Alternatively, this study aims to present a hybrid approach combining both receiver–receiver and sender–receiver schemes to reduce the variation of two-way message exchange durations, in heavy-load networks. To achieve network-wide synchronization, a variant of Prim’s algorithm (Cormen et al., 2009) is used to build a spanning tree, guaranteeing the minimum number of ancestors and limited error propagation. The simulation results show that the proposed approach is very competitive with a set of the most-cited synchronization protocols. In addition, a new synchronization simulator SynSim was developed using C++ language

To achieve network-wide synchronization, a variant of Prim's algorithm (Cormen et al., 2009) is used to build a spanning tree, guaranteeing the minimum number of ancestors and limited error propagation.

Simulation results show that the proposed approach is very competitive with a set of the most-cited synchronization protocols. In addition, a new synchronization simulator SynSim was developed using in C++ language.

It can be concluded from the experiments that MDSP is suitable for WSNs especially if MAC layer timestamping is not possible. So, the mean delays synchronization protocol (MSDP) is suitable to achieve time synchronization in single-hop and multi-hop networks without the MAC layer timestamping in large wireless sensor network (WSN) deployments.

A future enhancement of MDSP could be switching between the traditional timestamping and the new proposed timestamping based on a given threshold, which is the number of nodes in the neighborhood and the load of the network. It will be also interesting to test it in a prototype. The proposed solution can be used in practice to implement the Time-division multiple access (TDMA) protocol in a WSN. In addition, the proposed simulator can be used in a computer network synchronization protocols course.

To the best of authors’ knowledge, this study’s contribution is original. In addition, the authors implemented a new synchronization simulator

The face recognition problem has a long history and a significant practical perspective and one of the practical applications of the theory of pattern recognition, to automatically localize the face in the image and, if necessary, identify the person in the face. Interests in the procedures underlying the process of localization and individual’s recognition are quite significant in connection with the variety of their practical application in such areas as security systems, verification, forensic expertise, teleconferences, computer games, etc. This paper aims to recognize facial images efficiently. An averaged-feature based technique is proposed to reduce the dimensions of the multi-expression facial features. The classifier model is generated using a supervised learning algorithm called a back-propagation neural network (BPNN), implemented on a MatLab R2017. The recognition rate and accuracy of the proposed methodology is comparable with other methods such as the principle component analysis and linear discriminant analysis with the same data set. In total, 150 faces subjects are selected from the Olivetti Research Laboratory (ORL) data set, resulting 95.6 and 85 per cent recognition rate and accuracy, respectively, and 165 faces subjects from the Yale data set, resulting 95.5 and 84.4 per cent recognition rate and accuracy, respectively.

Averaged-feature based approach (dimension reduction) and BPNN (generate supervised classifier).

The recognition rate is 95.6 per cent and recognition accuracy is 85 per cent for the ORL data set, whereas the recognition rate is 95.5 per cent and recognition accuracy is 84.4 per cent for the Yale data set.

Averaged-feature based method.

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.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

The purpose of this paper is to present a new way of manufacturing process in the plant of the leading weedicide manufacturing company in Korea, Dongbu.

This paper explains a design of Auto‐ID based weedicide manufacturing process, introduces new mechanism for assembly machine and presents simulation approach to understand potential benefit.

In Dongbu, there was no information matching among bottle, box and pallet levels. Another issue was error propagation. Because, the allowance range for weight difference is different depending on the level of unit, the small weight difference (i.e. deviation) within allowance range in bottle level can create errors when accumulated for boxing. The proposed method improved performance measures such as cycle time and cost of raw materials by introducing Auto‐ID technology. As in the simulation results, it is considered that adoption of radio frequency identification together with this automatic module will improve manufacturing performance drastically.

The research was based on the real world implementation of Auto‐ID based manufacturing in weedicide manufacturing company and discussed a new approach which addresses the current issues of industry.