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Complex mechanical 3D computer-aided design (CAD) model embodies rich implicit design knowledge. Through discovering the key function parts and key function module in 3D CAD assembly model in advance, it can promote the designers’ understanding and reuse efficiency of 3D assembly model in design reuse.

An approach for discovering key function module in complex mechanical 3D CAD assembly model is proposed. First, assembly network for 3D CAD assembly model is constructed, where the topology structure characteristics of 3D assembly model are analyzed based on complex network centrality. The degree centrality, closeness centrality, betweenness centrality and mutual information of node are used to evaluate the importance of the parts in 3D assembly model. Then, a multi-attribute decision model for part-node importance is established, and the comprehensive evaluation for key function parts in 3D assembly model is accomplished by combining Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Subsequently, a community discovery of function module in assembly model-based Clauset–Newman–Moore (CNM)-Centrality is given in details. Finally, 3D CAD assembly model of worm gear reducer is taken as an example to verify the effectiveness and feasibility of proposed method.

The key function part in CAD assembly model is evaluated comprehensively considering assembly topology more objectively. In addition, the key function module containing key function part is discovered from CAD assembly model by using CNM-Centrality-based community discovery.

The approach can be used for discovering important design knowledge from complex CAD assembly model when reusing the assembly model. It can help designers capture and understand the design thinking and intent, improve the reuse efficiency and quality.

The paper first proposes an approach for discovering key function module in complex mechanical 3D CAD assembly model taking advantage of complex network theory, where the key function part is evaluated using node centrality and TOPSIS, and the key function module is identified based on community discovery.

Three-dimensional computer-aided design (CAD) assembly model has become important resource for design reuse in enterprises, which implicates plenty of design intent, assembly intent, design experience knowledge and functional structures. To acquire quickly CAD assembly models associated with specific functions by using product function requirement information in the product conceptual design phase for model reuse, this paper aims to find an approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model before functional semantic-based assembly retrieval.

An approach for structure-function correlations analysis and functional semantic annotation of CAD assembly model is proposed. First, the product knowledge model is constructed based on ontology including design knowledge and function knowledge. Then, CAD assembly model is represented by part attributed adjacency graph and partitioned into multiple functional regions. Assembly region and flow-activity region are defined for structure-function correlations analysis of CAD assembly model. Meanwhile, the extraction process of assembly region and flow-activity region is given in detail. Furthermore, structure-function correlations analysis and functional semantic annotation are achieved by considering comprehensively assembly structure and assembled part shape structure in CAD assembly model. After that, a structure-function relation model is established based on polychromatic sets for expressing explicitly and formally relationships between functional structures, assembled parts and functional semantics.

The correlation between structure and function is analyzed effectively, and functional semantics corresponding to structures in CAD assembly model are labeled. Additionally, the relationships between functional structures, assembled parts and functional semantics can be described explicitly and formally.

The approach can be used to help designers accomplish functional semantic annotation of CAD assembly models in model repository, which provides support for functional semantic-based CAD assembly retrieval in the product conceptual design phase. These assembly models can be reused for product structure design and assembly process design.

The paper proposes a novel approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model. Functional structures in assembly model are extracted and analyzed from the point of view of assembly structure and function part structure. Furthermore, the correlation relation between structures, assembled parts and functional semantics is expressed explicitly and formally based on polychromatic sets.

The purpose of this paper is to find a method for key assembly structure identification in complex mechanical assembly. Three-dimensional model reuse plays an increasingly important role in complex product design and innovative design. Assembly model has become important resource of models reuse in enterprises, which contains certain function assembly structures. These assembly structures implicating plenty of design intent and design experience knowledge can be used to support function-structure design, modular design reuse and semantics analysis for complex product.

A method for identifying key assembly structures in assembly model is presented from the viewpoint of assembly topology and multi-source attributes. First, assembly model is represented based on complex network. Then, a two-level evaluation model is put forward to evaluate importance of parts assembled, and the key function parts in assembly can be obtained. After that, on the basis of the function parts, a heuristic algorithm upon breadth first searching is given to identify key assembly structures.

The method could be used to evaluate key function parts and identify key assembly structures in complex mechanical assembly according to the specific circumstances.

The method can not only help designers find the key assembly structure in complex mechanical assembly model, facilitate the function-structure designing and semantics analyzing, and thereby improve the efficiency of product knowledge reuse, but also assist in analyzing influence scope of key function part changing and optimization of the assembly process for complex mechanical assembly.

The paper is the first to propose a method for key assembly structure identification in complex mechanical assembly, where the key function parts can be evaluated through a two-level evaluation model, and the key assembly structures are identified automatically based on complex network.

In this paper, the authors take an amorphous flattened air-ground wireless self-assembling network system as the research object and focus on solving the wireless self-assembling network topology instability problem caused by unknown control communication faults during the operation of this system.

In the paper, the authors propose a neural network-based direct robust adaptive non-fragile fault-tolerant control algorithm suitable for the air-ground integrated wireless ad hoc network integrated system.

The simulation results show that the system eventually tends to be asymptotically stable, and the estimation error asymptotically tends to zero with the feedback adjustment of the designed controller. The system as a whole has good fault tolerance performance and autonomous learning approximation performance. The experimental results show that the wireless self-assembled network topology has good stability performance and can change flexibly and adaptively with scene changes. The stability performance of the wireless self-assembled network topology is improved by 66.7% at maximum.

The research results may lack generalisability because of the chosen research approach. Therefore, researchers are encouraged to test the proposed propositions further.

This paper designs a direct, robust, non-fragile adaptive neural network fault-tolerant controller based on the Lyapunov stability principle and neural network learning capability. By directly optimizing the feedback matrix K to approximate the robust fault-tolerant correction factor, the neural network adaptive adjustment factor enables the system as a whole to resist unknown control and communication failures during operation, thus achieving the goal of stable wireless self-assembled network topology.

Haptics can significantly enhance the user's sense of immersion and interactivity. Especially in an assembly task, haptic feedback can help designers to have a better understanding of virtual objects and to increase task efficiency. The purpose of this paper is to investigate the design and implementation of a haptic‐based virtual assembly system (HVAS).

A multi‐thread system structure was designed, an automatic data integration interface was developed to transfer geometry, topology, assembly and physics information from a computer‐aided design system to virtual reality application, and a hierarchical constraint‐based data model and scene graph structure was designed to construct the virtual assembly environment. Unlike traditional virtual assembly systems based on collision detection or geometry constraint only, a physics‐based modeling approach combining with haptic feedback and geometry constraint was undertaken to realize and guide the realistic assembly process. When two parts collide into each other, the force and torque can be computed and provide feedback, and a spring‐mass model is used to prevent penetration and simulate dynamic behaviour. When two parts are close enough to each other and the assembly simulation state is activated, a geometry constraint can be captured, an attractive force can be generated to guide the user to assemble the part along the correct position, and the repulsive force can also be generated to realize the mating process as natural and realistic as in real life.

The implementation details and application examples demonstrate that haptic‐based virtual assembly is a valuable tool for assembly design and process planning.

The paper presents an HVAS.

Virtual assembly (VA) based on virtual reality (VR) is a key technique of virtual manufacturing. It provides not only an intuitive and interactive interface for virtual product design, but also an efficient method to analyze or verify assembly performance of these products. Preliminary investigations of constructing a VA system were implemented in this paper. There were three key techniques in constructing a VA system, which were data transformation from CAD system to VA system, collision detection, and virtual manipulation with a virtual hand. These key techniques were analyzed further and their concrete algorithms were given. At last an experimental VA system was set‐up to verify these algorithms. It is proved that the transformed data are sufficient, which can satisfy the VA system's requirement; the collision detection algorithm is efficient as it assures the system to be real time; and the virtual manipulation algorithm guarantees the system's reality and maneuverability.

For compactness and ease in assembling, a novel miniature size tubular moving magnet linear oscillating actuator (MT-MMLOA) design for miniature linear compressor application is proposed in this paper.

This MT-MMLOA design possesses a modular C-core stator structure having separation at the middle. Axially magnetized tubular permanent magnets are accommodated on the mover. To improve the output parameters of the linear oscillating actuators (LOA), all the design parameters are optimized using a parametric sweep. Finite element analysis of the proposed design is performed to examine the magnetic flux density as well as thrust force under both static and dynamic analysis within the intended stroke range.

Compared to conventional LOA for miniature compressors, the motor constant of the proposed LOA is 37 N/A that is 85% greater while keeping the same size of LOA. Permanent magnet volume used in the investigated topology of LOA is 26% reduced. Additionally, the overall volume of the machine is 10.3% decreased. Furthermore, the proposed topology is simple, inexpensive and easy to manufacture.

Electromagnetic performance comparison with different topologies proposed earlier in literature is carried out to prove the performance superiority of the proposed design.

The purpose of this paper is to provide a knowledge-enabled digital twin for smart design (KDT-SD) of aircraft assembly line (AAL) to enhance the AAL efficiency, performance and visibility. Modern AALs usually need to have capabilities such as digital-physical interaction and self-evaluation that brings significant challenges to traditional design method for AAL. The digital twin (DT) combining with reusable knowledge, as the key technologies in this framework, is introduced to promote the design process by configuring, understanding and evaluating design scheme.

The proposed KDT-SD framework is designed with the introduction of DT and knowledge. First, dynamic design knowledge library (DDK-Lib) is established which could support the various activities of DT in the entire design process. Then, the knowledge-driven digital AAL modeling method is proposed. At last, knowledge-based smart evaluation is used to understand and identify the design flaws, which could further improvement of the design scheme.

By means of the KDT-SD framework proposed, it is possible to apply DT to reduce the complexity and discover design flaws in AAL design. Moreover, the knowledge equips DT with the capacities of rapid modeling and smart evaluation that improve design efficiency and quality.

The proposed KDT-SD framework can provide efficient design of AAL and evaluate the design performance in advance so that the feasibility of design scheme can be improved as much as possible.

The paper aims to present the processing pipeline of an assembly immersive simulation application which can manage the interaction between the virtual scene and user using stereoscopic display and haptic devices. A new set of elements are integrated in a Collaborative Virtual Environment (CVE) and validated using an approach based on subjective and objective users’ performance criteria. The developed application is intended for Assembly/Disassembly (A/D) analysis, planning and training.

A mobility module based on contact information is used to handle the assembly components’ movements through real-time management of collision detection and kinematically constraint guidance. Information on CVE architecture, modules and application configuration process are presented. Impact of device type (3 degrees of freedom (DoFs) vs 6 DoFs) over user’s experience is evaluated. Parameters (number of assembled components and components assembly time) are measured for each user and each haptic device, and results are compared and discussed.

Test results proved the efficiency of using a mobility module based on predefined kinematic constraints for reducing the complexity of collision detection algorithms in real-time assembly haptic simulations. Also, experiments showed that, generally, users performed better with 3 DoFs haptic device compared to 6 DoFs haptic equipment.

The proposed immersive application automates the kinematical joints inference from 3D computer-aided design (CAD) assembly models and integrates it within a haptic-based virtual environment, for increasing the efficiency of A/D process simulations.

The purpose of this paper is to propose a novel mathematical model to present the three-dimensional tolerance of a discrete surface and to carry out an approach to analyze the tolerance of an assembly with a discrete surface structure. A discrete surface is a special structure of a large surface base with several discrete elements mounted on it, one, which is widely used in complex electromechanical products.

The geometric features of discrete surfaces are separated and characterized by small displacement torsors according to the spatial relationship of discrete elements. The torsor cluster model is established to characterize the integral feature variation of a discrete surface by integrating the torsor model. The influence and accumulation of the assembly tolerance of a discrete surface are determined by statistical tolerance analysis based on the unified Jacobian-Torsor method.

The effectiveness and superiority of the proposed model in comprehensive tolerance characterization of discrete surfaces are successfully demonstrated by a case study of a phased array antenna. The tolerance is evidently and intuitively computed and expressed based on the torsor cluster model.

The tolerance analysis method proposed requires much time and high computing performance for the calculation of the statistical simulation.

The torsor cluster model achieves the three-dimensional tolerance representation of the discrete surface. The tolerance analysis method based on this model predicts the accumulation of the tolerance of components before their physical assembly.

This paper proposes the torsor cluster as a novel mathematical model to interpret the tolerance of a discrete surface.