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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.

This paper aims to provide a new method of generating relatively accurate and smooth saturated B-H curves based on reliable measurement data to improve the accuracy and efficiency of electromagnetic simulation.

The characteristics of different B-H curve extrapolation models are summarized, and an improved method is proposed. The fitting procedure in low fields and extrapolation procedure in high fields are presented in detail. The saturated B-H curves generated by various methods are compared and discussed. Finally, a simulation case study proved the advantages of the new method in terms of simulation accuracy and efficiency.

The B-H curve created by the new method avoids extrapolation from a single point and simultaneously smoothens the entire B-H curve, thereby improving the simulation accuracy and efficiency. The low magnetic potential requirements for closed measurements and the small deviation with open measurements indicate that this method is well-suited for implementation.

The results are applicable for materials subject to such excitation levels that saturation has to be taken into account.

While some extrapolation models of B-H curves have been investigated in reference papers, there is still room for improvement in accuracy and smoothness. The new method processes low fields and high fields magnetization data and then connects them based on third-order boundary equations for the first time. This method can generate saturated B-H curves with good accuracy and smoothness while retaining outstanding operability.

In an intelligent transportation system (for short, ITS) environment, a vehicle’s motion is affected by the information in a large scale. The purpose of this paper is to study the integration effect of multiple vehicles’ delayed velocities on traffic flow.

This paper constructed a new car-following model to study the integration effect of multiple vehicles’ delayed velocities on traffic flow. The new model is analyzed by linear and nonlinear perturbation method theoretically and also verified by simulation.

It is found out that the integration of preceding vehicles’ delayed velocities affect the stability of traffic flow importantly, and three preceding vehicles’ delayed velocities information should be considered in real traffic.

The new car-following model by considering the integration effect of multiple vehicles’ delayed velocities is firstly proposed in this paper. The research result shows that three preceding vehicles’ delayed velocities information is the best choice to stabilizing traffic flow.

Crane plays a very important role in national economy with greatly reduced labor intensity, improved production efficiency and promoted social development as an indispensable auxiliary tool and process equipment. Therefore, its energy consumption becomes an unavoidable topic and in fact, energy consumption of crane is very huge. It has been proved to be the most cost-effective way for reducing energy consumption to establish and implement new energy efficiency standard. Thus, it is necessary to analyze and evaluate the energy efficiency for overhead crane so as to propose a new energy efficiency standard. The paper aims to discuss these issues.

In this paper, four kinds of energy consumption sources of overhead crane is considered, based on which, an energy efficiency grading model for overhead crane based on BP neural network is proposed. Second, DS evidential theory is analyzed and based on it, an energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed. The evaluation procedure is discussed in detail. Then, a case is demonstrated how the evaluation is carried out.

If overhead cranes with different energy consumptions need to be graded according to energy efficiency, the criterions to establish the energy efficiency labels for overhead cranes is proposed in this paper.

The research results can provide energy efficiency standard proposal of overhead crane for relative departments to monitor the design, manufacturing and use of overhead crane.

An energy efficiency grading model for overhead crane based on BP neural network is proposed. An energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed.

This purpose of this paper is to design a peg-in-hole controller for a cable-driven serial robot with compliant wrist (CDSR-CW) using cable tensions and joint positions. The peg is connected to the robot link through a CW. It is required that the controller does not rely on any external sensors such as 6-axis wrist force/torque (F/T) sensor, and only the compliance matrix’s estimated value of the CW is known.

First, the peg-in-hole assembly system based on a CDSR-CW is analyzed. Second, a characterization algorithm using micro cable tensions and joint positions to express the elastic F/T at the CW is established. Next, under the premise of only knowing the compliance matrix’s estimate, a peg-in-hole controller based on force/position hybrid control is proposed.

The experiment results show that the plug contact F/T can be tracked well. This verifies the validity and correctness of the characterization algorithm and peg-in-hole controller for CDSR-CWs in this paper.

First, to the authors’ knowledge, there is no relevant work about the peg-in-hole assembly task using a CDSR-CW. Besides, the proposed characterization algorithm for the elastic F/T makes the peg-in-hole controller get rid of the dependence on the F/T sensor, which expands the application scenarios of the peg-in-hole controller. Finally, the controller does not require an accurate compliance matrix, which also increases its applicability.

This paper aims to perform experimental test on fatigue characteristics of package on package (POP) stacked chip assembly under thermal cycling load. Some suggestions for design to prolong fatigue life of POP stacked chip assembly are provided.

The POP stacked chip assembly which contains different package structure mode and chip position was manufactured. The fatigue characteristics of POP stacked chip assembly under thermal cycling load were tested. The fatigue load spectrum of POP stacked chip assembly under thermal cycling load was given. The fatigue life of chips can be estimated by using the creep–fatigue life prediction model based on different stress conditions.

The solder joint stress of top package is significantly less than that of bottom solder joints, and the maximum value occurs in the middle part of the solder joints inner ring.

This paper fulfils useful information about the thermal reliability of POP stacked chip assembly with different structure characteristics and materials parameters.

The purpose of this paper is to expound the relationship among microstructure, mechanical property, tribological behavior and deformation mechanism of carburized layer deposited on Ti-6Al-4V alloy by double-glow plasma hydrogen-free carburizing surface technology.

Morphologies and phase compositions of the carburized layer were observed by scanning electron microscope and X-ray diffraction. The micro-hardness tests were used to evaluate the surface and cross-sectional hardness of carburized layer. The reciprocating friction and wear experiments under various load conditions were implemented to investigate the tribological behavior of carburized layer. Moreover, scratch test with ramped loading pattern was carried out to illuminate the deformation mechanism of carburized layer.

Compared to substrate, the hardness of surface improved to ∼1,100 HV_0.1, while the hardness profile of carburized layer presented gradual decrease from ∼1,100 to ∼300 HV_0.1 within the distance of the total carburizing-affected region about 30 µm. The coefficient of friction, wear rate and wear morphology of carburized layer were analyzed. Scratch test indicated that the deformation process of carburized layer could be classified into three mechanisms (elastic, changing elastic–plastic and stable elastic–plastic mechanisms), and the deformation transition of the carburizing-affected region was from changing elastic–plastic to elastic mechanisms. Both the elastic and changing elastic–plastic mechanisms are conducive to the wearing course.

Using this technology, hydrogen embrittlement was avoided and wear resistance property of titanium alloy was greatly improved. Simultaneously, the constitutive relation during the whole loading process was deduced in terms of scratch approach, and the deformation mechanism of carburized layer was discussed from a novel viewpoint.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2019-0489/

Reorganising unstructured academic abstracts according to a certain logical structure can help scholars not only extract valid information quickly but also facilitate the faceted search of academic literature. This study aims to build a high-performance model for identifying of the functional structures of unstructured abstracts in the social sciences.

This study first investigated the structuring of abstracts in academic articles in the field of social sciences, using large-scale statistical analyses. Then, the functional structures of sentences in the abstract in a corpus of more than 3.5 million abstracts were identified from sentence classification and sequence tagging by using several models based on either machine learning or a deep learning approach, and the results were compared.

The results demonstrate that the functional structures of sentences in abstracts in social science manuscripts include the background, purpose, methods, results and conclusions. The experimental results show that the bidirectional encoder representation from transformers exhibited the best performance, the overall F1 score of which was 86.23%.

The data set of annotated social science abstract is generated and corresponding models are trained on the basis of the data set, both of which are available on Github (https://github.com/Academic-Abstract-Knowledge-Mining/SSCI_Abstract_Structures_Identification). Based on the optimised model, a Web application for the identification of the functional structures of abstracts and their faceted search in social sciences was constructed to enable rapid and convenient reading, organisation and fine-grained retrieval of academic abstracts.

The successful and commercial use of self-driving/driverless/unmanned/automated car will make human life easier. The paper aims to discuss this issue.

This paper reviews the key technology of a self-driving car. In this paper, the four key technologies in self-driving car, namely, car navigation system, path planning, environment perception and car control, are addressed and surveyed. The main research institutions and groups in different countries are summarized. Finally, the debates of self-driving car are discussed and the development trend of self-driving car is predicted.

This paper analyzes the key technology of self-driving car and illuminates the state-of-art of the self-driving car.

The main research contents and key technology have been introduced. The research progress as well as the research institution has been summarized.

Industry 4.0 envisions a future of networked production where interconnected machines and business processes running in the cloud will communicate with one another to optimize production and enable more efficient and sustainable individualized/mass manufacturing. However, the openness and process transparency of networked production in hyperconnected manufacturing enterprises pose severe cyber-security threats and information security challenges that need to be dealt with. The paper aims to discuss these issues.

This paper presents a distributed trust model and middleware for collaborative and decentralized access control to guarantee data transparency, integrity, authenticity and authorization of dataflow-oriented Industry 4.0 processes.

The results of a performance study indicate that private blockchains are capable of securing IoT-enabled dataflow-oriented networked production processes across the trust boundaries of the Industry 4.0 manufacturing enterprise.

This paper contributes a decentralized identity and relationship management for users, sensors, actuators, gateways and cloud services to support processes that cross the trust boundaries of the manufacturing enterprise, while offering protection against malicious adversaries gaining unauthorized access to systems, services and information.