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The purpose of this paper is to study the integration between this technology and barrel finishing (BF) operation to improve part surface quality. Fused deposition modeling (FDM) processes have limitation in term of accuracy and surface finishing. Hence, post-processing operations are needed. A theoretical and experimental investigations have been carried out.

A geometrical model of the profile under the action of machining is proposed. The model takes into account FDM formulation and allows to predict the surface morphology achievable by BF. The MR needed in the model is obtained by a particular profilometer methodology, based on the alignment of Firestone–Abbot (F–A) curves. The experimental performed on a suitable geometry validated geometrical model. Profilometer and dimensional measurements have been used to assess the output of the coupled technologies in terms of surface roughness and accuracy.

The coupling of FDM and BF has been assessed and characterized in terms of obtained part surfaces and dimension evolution. Deposition angle strongly affects the BF removal speed and alters nominal dimensions of part. The geometric profile model gave interesting information about profile morphology and machining mechanism; moreover, the height prevision allows to estimate BF working time to accomplish part requirements.

The prediction of the geometric profile as a function of FDM fabrication parameters is a powerful tool which permits to investigate surface properties such as mechanical coupling or tribological aspects. The coupling of BF and FDM has been assessed and now optimization of this process can be performed just evaluating effects of parameters.

This research has been focused to an industrial application, and results can be used in a computer-aided manufacturing. The prevision of surface obtainable by this integration is a tool to find the part optimum orientation to accomplish the drawing requirements. Both the experimental findings and the model can guide operator toward a proper process improvement, thus reducing or eliminating expensive trial and error phase in the post-processing operation of FDM prototypes.

In this paper, a novel model has been presented. It allows to know in advance profile morphology achievable by a specific surface of a FDM part after a determined BF working time. A particular application of FA curves gives the MR values.

A three-dimensional (3D) printing error simulation approach is proposed to analyze the influence of tilted vertical beams on the 3D printing accuracy. The purpose of this study is to analyze the influence of such errors on printing accuracy and printing quality for delta-robot 3D printer.

First, the kinematic model of a delta-robot 3D printer with an ideal geometric structure is proposed by using vector analysis. Then, the normal kinematic model of a nonideal delta-robot 3D robot with tilted vertical beams is derived based on the above ideal kinematic model. Finally, a 3D printing error simulation approach is proposed to analyze the influence of tilted vertical beams on the 3D printing accuracy.

The results show that tilted vertical beams can indeed cause 3D printing errors and further influence the 3D printing quality of the final products and that the 3D printing errors of tilted vertical beams are related to the rotation angles of the tilted vertical beams. The larger the rotation angles of the tilted vertical beams are, the greater the geometric deformations of the printed structures.

Three vertical beams and six horizontal beams constitute the supporting parts of the frame of a delta-robot 3D printer. In this paper, the orientations of tilted vertical beams are shown to have a significant influence on 3D printing accuracy. However, the effect of tilted vertical beams on 3D printing accuracy is difficult to capture by instruments. To reveal the 3D printing error mechanisms under the condition of tilted vertical beams, the error generation mechanism and the quantitative influence of tilted vertical beams on 3D printing accuracy are studied by simulating the parallel motion mechanism of a delta-robot 3D printer with tilted vertical beams.

The purpose of this research is to develop a kind of new service‐driven MEMS “top‐down” design method and implement the correspondent web‐based software prototype as verification.

Bond graphs are used as the output of conceptual design. Feature modeling technology is just a bridge to perform the feature mapping from the conceptual model to the structure and geometric model of micro‐components. To support design evaluations, a 3D whiteboard collaborative mechanism powered with networked VR service functions is put forward to visualize and operate small micro‐components in a macro world. In addition, service‐driven MEMS “top‐down” design flow is modeled as a formalized “AND/OR” graph with which the design service scheduling is finished with the priority‐in‐depth searching algorithm.

Traditional MEMS CAD systems were developed on the basis of “bottom‐up” design method mainly used in laboratory practice. Different from the above, this research presents a solution, which can outline a new service‐driven MEMS CAD model and decrease designers' dependency to manufacturing knowledge.

It is still necessary to study further how to create a much more efficient feature modeling mechanism to enable design evaluation for micro manufacturing.

The new design method and the correspondent software prototyping would potentially help industry to promote the development of new MEMS CAD systems.

The value is to identify a kind of new MEMS CAD implementation mode, which is suitable for general design uses on network.

This paper aims to propose a consistent approach to geometric modeling of optimized lattice structures for additive manufacturing technologies.

The proposed method applies subdivision surfaces schemes to an automatically defined initial mesh model of an arbitrarily complex lattice structure. The approach has been developed for cubic cells. Considering different aspects, five subdivision schemes have been studied: Mid-Edge, an original scheme proposed by the authors, Doo–Sabin, Catmull–Clark and Bi-Quartic. A generalization to other types of cell has also been proposed.

The proposed approach allows to obtain consistent and smooth geometric models of optimized lattice structures, overcoming critical issues on complex models highlighted in literature, such as scalability, robustness and automation. Moreover, no sharp edge is obtained, and consequently, stress concentration is reduced, improving static and fatigue resistance of the whole structure.

An original and robust method for modeling optimized lattice structures was proposed, allowing to obtain mesh models suitable for additive manufacturing technologies. The method opens new perspectives in the development of specific computer-aided design tools for additive manufacturing, based on mesh modeling and surface subdivision. These approaches and slicing tools are suitable for parallel computation, therefore allowing the implementation of algorithms dedicated to graphics cards.

The purpose of this paper is to propose a three-dimensional (3D) assembly model retrieval method based on assembling semantic information to address semantic mismatches, poor accuracy and low efficiency in existing 3D assembly model retrieval methods.

The paper proposes an assembly model retrieval method. First, assembly information retrieval is performed, and 3D models that conform to the design intention of the assembly are found by retrieving the code. On this basis, because there are conjugate subgraphs between attributed adjacency graphs (AAG) that have an assembly relationship, the assembly model geometric retrieval is translated into a problem of finding AAGs with a conjugate subgraph. Finally, the frequent subgraph mining method is used to retrieve AAGs with conjugate subgraphs.

The method improved the efficiency and accuracy of assembly model retrieval.

The examples illustrate the specific retrieval process and verify the feasibility and reasonability of the assembly model retrieval method in practical applications.

The assembly model retrieval method in the paper is an original method. Compared with other methods, good results were obtained.

This paper aims to propose a framework for optimizing the pose in the assembly process of the non-ideal parts considering the manufacturing deviations and contact deformations. Furthermore, the accuracy of the method would be verified by comparing it with the other conventional methods for calculating the optimal assembly pose.

First, the surface morphology of the parts with manufacturing deviations would be modeled to obtain the skin model shapes that can characterize the specific geometric features of the part. The model can provide the basis for the subsequent contact deformation analysis. Second, the simulated non-nominal components are discretized into point cloud data, and the spatial position of the feature points is corrected. Furthermore, the evaluation index to measure the assembly quality has been established, which integrates the contact deformations and the spatial relationship of the non-nominal parts’ key feature points. Third, the improved particle swarm optimization (PSO) algorithm combined with the finite element method is applied to the process of solving the optimal pose of the assembly, and further deformation calculations are conducted based on interference detection. Finally, the feasibility of the optimal pose prediction method is verified by a case.

The proposed method has been well suited to solve the problem of the assembly process for the non-ideal parts with complex geometric deviations. It can obtain the reasonable assembly optimal pose considering the constraints of the surface morphological features and contact deformations. This paper has verified the effectiveness of the method with an example of the shaft-hole assembly.

The method proposed in this paper has been well suited to the problem of the assembly process for the non-ideal parts with complex geometric deviations. It can obtain the reasonable assembly optimal pose considering the constraints of the surface morphological features and contact deformations. This paper has verified the method with an example of the shaft-hole assembly.

The different surface morphology influenced by manufacturing deviations will lead to the various contact behaviors of the mating surfaces. The assembly problem for the components with complex geometry is usually accompanied by deformation due to the loading during the contact process, which may further affect the accuracy of the assembly. Traditional approaches often use worst-case methods such as tolerance offsets to analyze and optimize the assembly pose. In this paper, it is able to characterize the specific parts in detail by introducing the skin model shapes represented with the point cloud data. The dynamic changes in the parts' contact during the fitting process are also considered. Using the PSO method that takes into account the contact deformations improve the accuracy by 60.7% over the original method that uses geometric alignment alone. Moreover, it can optimize the range control of the contact to the maximum extent to prevent excessive deformations.

This paper describes how non‐orthogonal geometric models may be transformed into orthogonal polyhedral models. The main purpose of the transformation is to obtain a geometric model that is easy to describe and further modify without loss of topological information from the original model.

The transformation method presented in this paper is based on fuzzy logic (FL). The idea of using FL for this type of transformation was first described by Takahashi and Shimizu. This paper describes both philosophy and techniques behind the transformation method as well as its application to some example 2D and 3D models. The problem in this paper is to define a transformation technique that will change a non‐orthogonal model into a similar orthogonal model. The orthogonal model is unknown at the start of the transformation and will only be specified once the transformation is complete. The model has to satisfy certain conditions, i.e. it should be orthogonal.

The group of non‐orthogonal models that contain triangular faces such as tetrahedra or pyramids cannot be successfully recognized using this method. This algorithm fails to transform these types of problem because to do so requires modification of the structure of the model. It appears that only when the edges are divided into pieces and the sharp angles are smoothed then the method can be successfully applied. Even though the method cannot be applied to all geometric models many successful examples for 2D and 3D transformation are presented. Orthogonal models with the same topology, which make them easier to describe, are obtained.

This transformation makes it possible to apply simple algorithms to orthogonal models enabling the solution of complex problems usually requiring non‐orthogonal models and more complex algorithms.

The aim of this study is to make a contribution towards reducing the deflections of silicon wafers. The deformation of silicon wafers used in the manufacture of electronic micro-components is one of the most common problems encountered by industrialists during manufacturing. Stack warping is typically produced during the process of depositing thin layers on a substrate. This is due to the thermal-mechanical stresses caused by the difference between the thermal expansion coefficients of the materials. Reducing wafer deformation is essential to increase reliability and improve quality. In this paper, the authors propose an approach based on minimal geometrical modifications to reduce the deformation of a silicon wafer coated with two thin layers. Numerical finite element models have been developed to evaluate the impact of geometrical modifications on warping amplitude. Finite element models have been validated compared with experimental models. The results obtained are encouraging and clearly show a considerable reduction in wafer deformation.

Reducing wafer deformation is essential to increase reliability and improve quality. In this paper, the authors propose an approach based on minimal geometrical modifications to reduce the deformation of a silicon wafer coated with two thin layers. Numerical finite element models have been developed to evaluate the impact of geometrical modifications on warping amplitude. Finite element models have been validated compared with experimental models.

The results obtained are encouraging and clearly show a considerable reduction in wafer deformation.

This paper describes the influence of geometric modification on wafer deformation. The work show also the cruciality of stress reduction in the purpose to obtain less wafer deformation.

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.

The purpose of this paper is to present an experimental approach to measure and quantify the three‐dimensional geometrical manufacturing errors on a mass production of parts.

A methodology is developed to model and analyse the combined effect of these errors on a machined feature. Deviation of a machined feature due to the combined errors is expressed in terms of the small displacement torsor (SDT) parameters. Given a tolerance on the machined feature, constraints are specified for that feature to establish a relationship between the tolerance zone of the feature and the torsor parameters. These constraints provide boundaries within which the machined feature must lie. This is used for tolerance analysis of the machined feature. An experimental approach is proposed to measure and quantify the three‐dimensional manufacturing variations as torsors. The results are used to verify the analytical model.

Results show that it is possible to quantify manufacturing dispersions. The paper proposes a measuring method which can be done during the production. In the context of process planning, these experimental data allow us to perform realistic geometrical simulation of manufacturing. The results of this method are torsor components dispersions. Analysis and synthesis of the geometrical simulation of manufacturing are viable with reliable numerical data in order to predict the defects.

To perform realistic geometrical simulation of manufacturing, an experimental approach to measure and quantify the three‐dimensional geometrical manufacturing errors is proposed which is based on the SDT concept.