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Propoes a methodology that enables a dynamic and interactive 3‐Dvisualization model of the assembly process to be developed from the CAD files of each part in the assembly. Makes three main contributions to the research in this area. First, a taxonomy of features for assembly is presented. Second, a process model for generating interactive 3D models of the assembly process is developed and, third, a new algorithm for creating a dynamic assembly model is derived. This algorithm, called the 3D assembly visualization (3AV) algorithm, involves instantiating the motion attributes that specify the motion of each part in the assembly. This dynamic assembly model is then converted to a 3‐D renderable format for visualization. An example is presented that uses virtual reality modeling language (VRML) as the 3‐D representation language. The result is a dynamic and interactive visual representation of the assembly operation. Such visualization can be of considerable use in DFA.

This paper aims to develop an assembly behaviour dynamic model of reheat stop valve assembly under run‐time situations and combined (assembly error, friction, fluid dynamics and thermal load behaviour) and to carry out assembly process evaluation and optimisation.

The fluid dynamic behaviour analysis is carried out for the dynamic torque characteristics of reheat stop valve and for the thermal load distribution of the valve shaft‐bush subassembly, which is used for evaluating the thermal deformation of valve shaft by using of finite elements method. The assembly behaviour dynamic model is developed by multibody dynamics theory, which is as the basis of developing virtual prototyping platform for analysing and evaluating the current assembly process.

It is revealed that the deformation (ε) of valve shaft due to the thermal load, and the assembly coaxial error (e) can change the motion clearance remarkably, which lead the dynamic properties and performance of reheat stop valve changed greatly. The current assembly behaviour variable are not optimum and the initial design clearance between valve shaft and bush 4# can be optimised by the developed virtual prototyping platform on the basis of ADAMS® API. The results of evaluation for the assembly behaviour reveal the well dynamic characteristics of reheat stop valve with the optimum assembly behaviour variable. This will be useful for improving the current assembly process of reheat stop valve.

The present assembly behaviour dynamic model based on virtual prototyping for optimum assembly process design uses only single objective optimisation (the most important clearance between valve shaft and bush 4#). For a complete optimum assembly process design has to be carried out with other three clearance variables (the clearance between valve shaft and bush 1#, bush 2# and bush 3#) together.

The present analysis provides some benchmarks for improving the current assembly process. In practice, the assembly coaxial tolerance of valve shaft‐bush subassembly and the initial design clearances must be limited strictly.

This paper provides a methodology for analysis and evaluation of reheat stop valve assembly behaviour with the consideration of combined environmental behaviours. Based on this methodology, it is possible to develop an assembly behaviour dynamic model, and further, to develop a virtual prototyping platform for analysing and evaluating the assembly process which will offer help to designers for improving the reheat stop valve assembly process.

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.

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.

This paper aims to provide a new dynamic modeling approach for root cause detection of the auto-body assembly variation.

The dynamic characteristics, such as fixture element wear and quality of incoming parts, are considered in assembly variation modeling with the dynamic Bayesian network. Based on the network structure mapping, the parameter learning of different types of nodes is conducted by integrating process knowledge and Monte Carlo simulation. The inference was that both the measurement data and maintenance actions are evidence for the improvement of diagnosis accuracy.

The proposed assembly variation model which has incorporated dynamic manufacturing features could be used to detect multiple process faults effectively.

A dynamic variation modeling method is proposed. This method could be used to provide more accurate diagnosis results and preventive maintenance guidelines for the assembly process.

This paper aims to propose cooperative control strategies for dual-arm robots in different human–robot collaborative tasks in assembly processes. The authors set three different regions where robot performs different collaborative ways: “teleoperate” region, “co-carry” region and “assembly” region. Human holds the “master” arm of dual-arm robot to operate the other “follower” arm by our proposed controller in “teleoperation” region. Limited by the human arm length, “follower” arm is teleoperated by human to carry the distant object. In the “co-carry” region, “master” arm and “follower” arm cooperatively carry the object to the region close to the human. In “assembly” region, “follower” arm is used for fixing the object and “master” arm coupled with human is used for assembly.

A human moving target estimated method is proposed for decreasing efforts for human to move “master” arm, radial basis functions neural networks are used to compensate for uncertainties in dynamics of both arms. Force feedback is designed in “master” arm controller for human to perceive the movement of “follower” arm. Experimental results on Baxter robot platform show the effectiveness of this proposed method.

Experimental results on Baxter robot platform show the effectiveness of our proposed methods. Different human-robot collaborative tasks in assembly processes are performed successfully under our cooperative control strategies for dual-arm robots.

In this paper, cooperative control strategies for dual-arm robots have been proposed in different human–robot collaborative tasks in assembly processes. Three different regions where robot performs different collaborative ways are set: “teleoperation” region, “co-carry” region and “assembly” region.

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.

In the high-speed trains (HSTs) production process, assembly sequence planning (ASP) problems is an extremely core issue. ASP problems influence the economic cost, amount of workers and the working time in the assembly process, seriously. In the design process of HSTs, the assembly sequence is usually given by experience, and the correctness of the assembly sequence is difficult to guarantee by experience and low effectiveness. The ASP based on improved discrete particle swarm optimization (IDPSO) algorithm was proposed to address these issues.

In view of the local convergence problem with basic DPSO in ASP, this paper presents an IDPSO, in which a chosen strategy of global optimal particle is introduced in, to solve the ASP problems in the assembly process of HSTs operation panel. The geometric feasibility, the assembly stability, and the number of assembly orientation changes of the assembly are chosen to be the optimization objective. Furthermore, the influences of the population size, the weight coefficient, and the learning factors to the stability and efficiency of IDPSO algorithm were discussed.

The results show that the IDPSO algorithm can obtain the global optimum efficiently, which is proved to be a more useful method for solving ASP problems than basic DPSO. The IDPSO approach could reduce the working time and economic cost of ASP problems in HSTs significantly.

The method may save the economic cost, reduce the amount of workers and save the time in the assembly process of HSTs. And also may change the method of ASP in design and manufacturing process, and make the production process in HSTs more efficiently.

A chosen strategy of global optimal particle is presented, which can overcome the local convergence problem with basic DPSO for solving ASP problems.

Product variant design process consists of a series of asynchronous activities. These activities and the logic relations among them are important in constructing general logic workflow structure, which is the foundation of deriving an activity path for variant design business. Traditional process modeling approaches have not defined activities for product variant design and cannot describe the complex relations among these activities because of the lack of logic express elements. Thus, logic workflow structure modeling method is anticipated to meet the requirements of logic description and path generation in product variant design application. This paper aims to address these issues.

The paper identifies the variant design modes of different types of parts and defines their variant design activities. The procedure of constructing general logic workflow structure of product variant design is proposed. Simultaneously, the principles of inferring logic relations among activities are put forward based on their adjacency information and connectivity probability. A general logic workflow structure of product variant design is constructed. Based on this, activity path corresponding to a variant design business can be generated. The algorithm of generating activity path is designed as well. In addition, Boolean vectors of activity path, based on the functional contour matrix of polychromatic set theory, can be inferred, which denotes the functional character of activity path.

A general logic workflow structure for product variant design has been established, which comprises variant design activities and basic process logic nodes. The logic relations among activities can be inferred based on their in-degree/out-degree and connectivity probability. The function character of activity path can also be expressed based on the polychromatic set theory.

The combination of variant design activity and basic process logic node makes diverse variant design business descriptions possible in a general workflow structure. The proposed approach provides evidences for designer to plan and develop product variant design system effectively.

In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.

This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.

In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.

The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.