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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.

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.

Owing to the numerous part models and massive datasets used in automobile assembly design, virtual assembly software cannot simulate a whole vehicle smoothly in real time. For this reason, implementing a new virtual assembly environment for massive complex datasets would be a significant achievement. The paper aims to focus on this problem.

A new system named “Grid‐enabled collaborative virtual assembly environment” (GCVAE) is proposed in the paper, and it comprises three parts: a private grid‐based support platform running on an inner network of enterprise; a service‐based parallel rendering framework with a sort‐last structure; and a multi‐user collaborative virtual assembly environment. These components would aggregate the idle resources in an enterprise to support assembly simulation with a large complex scene of whole vehicle.

The system prototype proposed in the paper has been implemented. The following simulations show that it can support a complex scene in a real‐time mode by using existing hardware and software, and can promote the efficient usage of enterprise resources.

Using the GCVAE, it is possible to aggregate the idle resources in an enterprise to run assembly simulations of a whole automobile with massively complex scenes, thus observably reducing fault occurrence rates in future manufacturing.

The paper introduces a new grid‐enabled methodology into research on collaborative virtual assembly system which can make the best use of idle resources in the enterprise to support assembly simulations with massively complex product models. A video‐stream‐based method was used to implement the system; this enables designers to participate ubiquitously in the simulation to evaluate the assembly of the whole automobile without hardware limitations.

The assembly quality of complex products is pivotal to their lifecycle performance. Assembly precision analysis (APA) is an effective method used to check the feasibility and quality of assembly. However, there is still a need for a systematic approach to be developed for APA of kinematic mechanisms. To achieve more accurate analysis of kinematic assembly, this paper aims to propose a precision analysis method based on equivalence of the deviation source.

A unified deviation vector representation model is adopted by considering dimension deviation, geometric deviation, joint clearance and assembly deformation. Then, vector loops and vector equations are constructed, according to joint type and deviation propagation path. A combined method, using deviation accumulation and sensitivity modeling, is applied to solve the kinematic APA of complex products.

When using the presented method, geometric form deviation, joint clearance and assembly deformation are considered selectively during tolerance modeling. In particular, the proposed virtual link model and its orientation angle are developed to determine joint deviation. Finally, vector loops and vector equations are modeled to express deviation accumulation.

The proposed method provides a new means for the APA of complex products, considering joint clearance and assembly deformation while improving the accuracy of APA, as much as possible.

The paper aims to propose a method to build environmental constraint region online in complex-shaped peg-in-hole assembly tasks.

Compared with conventional way which using computer-aided design (CAD) models of assembly parts to construct the environmental constraint region offline, the paper provides an online approach that consists of three aspects: modeling assembly parts through visual recognition, decomposing complex shapes into multiple primitive convex shapes and a numerical algorithm to simulate the peg-in-hole insertion contact. Besides, a contrast experiment is performed to validate the feasibility and effectiveness of the method.

The experiment result indicates that online construction takes less time than the offline way under the same task conditions. Furthermore, due to the CAD models of the parts are not required to be known, the method proposed in the paper has a broader application in most assembly scenarios.

With the improvement of customization and complexity of manufactured parts, the assembly of complex-shaped parts has drawn greater attention of many researchers. The assembly methods based on attractive region in environment (ARIE) have shown great performance to achieve high-precision manipulation with low-precision systems. The construction of environmental constraint region serves as an essential part of ARIE-based theory, directly affect the formulation and application of assembly strategies.

Assembly Sequence Planning integrating assembly Resources (ASPR) is a trend in industry. Because of the introduction of resource, the complexity of ASPR for complex product increases drastically; besides, the dynamic property of resource and the co‐existence of assembly sequence and disassembly sequence (ASDS) make the problems in ASPR more difficult. The dynamic assembly model (DAM) based on polychromatic sets (PS) theory was proposed to address these issues.

First, a strategy was presented to simplify ASPR, taking advantage of assembly sequence generated in the phase of assembly design which considers no resource. Secondly, the concept of DAM was discussed, and some principles/criteria for DAM modeling were generalized from experience. Then, the DAM was modeled by formalizing its incidence relations as PS matrix, and refined based on the formalized criteria, which were expressed as PS locating and collision relation models. Finally, an application case was studied to demonstrate the effectiveness of the method.

The approach could reduce the complexity of ASPR significantly, and was able to identify dynamic resource, model DAM and handle the co‐existence of ASDS effectively.

The method may change the manual pattern of ASPR in simulation environment, and become a potential tool to change the pattern of traditional ASP which comes to work from scratch, by utilizing the upstream information of product design.

Different from traditional assembly model, DAM was a local model which consists of partial components of product and resource, and the DAM‐based ASPR approach would make the computational complexity of product assembly become more linear than exponential.

Virtual assembly process plays an important role in assembly design of complex product and is typically time- and resource-intensive. This paper aims to investigate a dynamic assembly simplification approach in order to demonstrate and interact with virtual assembly process of complex product in real time.

The proposed approach regards the virtual assembly process of complex product as an incremental growth process of dynamic assembly. During the growth process, the current-assembled-state assembly model is simplified with appearance preserved by detecting and removing its invisible features, and the to-be-assembled components are simplified with assembly features preserved using conjugated subgraphs matching method based on an improved subgraph isomorphism algorithm.

The dynamic assembly simplification approach is applied successfully to reduce the complexity of computer aided design models during the virtual assembly process and it is proved by several cases.

A new assembly features definition is proposed based on the notion of “conjugation” to assist the assembly features recognition, which is a main step of the dynamic assembly simplification and has been translated into conjugated subgraphs matching problem. And an improved subgraph isomorphism algorithm is presented to address this problem.

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.

This paper aims to investigate an approach for mental fatigue detection and estimation of assembly operators in the manual assembly process of complex products, with the purpose of founding the basis for adaptive transfer and demonstration of assembly process information (API), and eventually making the manual assembly process smarter and more human-friendly.

The proposed approach detects and estimates the mental state of assembly operators by electroencephalography (EEG) signal recording and analysis in an engine assembly experiment. When the subjects perform assembly tasks, their EEG signal is recorded by a portable EEG recording system called Emotiv EPOC+ headset. The feature set of the EEG signal is then extracted by calculating its power spectrum density (PSD), followed by data dimension reduction based on principal component analysis (PCA). The dimension-reduced data are classified by using support vector machines (SVMs), and hence, the mental state of assembly operators can be estimated during the assembly process.

The experimental result shows that the proposed approach is able to estimate the mental state of assembly operators within an acceptable accuracy range, and the PCA-based dimension reduction method performs very well by representing the high-dimensional EEG feature set with just a few principal components.

This paper provides theoretical and experimental basis for the API transfer and demonstration based on human cognition. It provides a new idea to seek balance between the improvement of production efficiency and the sustainable utilization of human resources.

The purpose of this paper is to present an analytical method for throughput analysis of assembly systems with complex structures during transients.

Among the existing studies on the performance evaluation of assembly systems, most focus on the system performance in steady state. Inspired by the transient analysis of serial production lines, the state transition matrix is derived considering the characteristics of merging structure in assembly systems. The system behavior during transients is described by an ergodic Markov chain, with the states being the occupancy of all buffers. The dynamic model for the throughput analysis is solved using the fixed-point theory.

This method can be used to predict and evaluate the throughput performance of assembly systems in both transient and steady state. By comparing the model calculation results with the simulation results, this method is proved to be accurate.

This proposed modeling method can depict the throughput performance of assembly systems in both transient and steady state, whereas most exiting methods can be used for only steady-state analysis. In addition, this method shows the potential for the analysis of complex structured assembly systems owing to the low computational complexity.