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Support structures are often needed in additive manufacturing (AM) to print overhangs. However, they are the extra materials that must be removed afterwards. When the supports have many contacts to the model or are even enclosed inside some concavities, removing them is very challenging and has a risk of damaging the part. Therefore, the purpose of this paper is to develop a new type of tree-support, named Escaping Tree-Support (ET-Sup), which tries to build all the supports onto the build plate to minimize the number of contact points.

The methodology is to first classify the support points into three categories: clear, obstructed and enclosed. A clear point has nothing between it and the build plate; an obstructed point is not clear, but there exists a path for it to reach the build plate; and an enclosed point has no way to reach the build plate. With this classification, the path for the obstructed points to come clear can be found through linking them to the clear points. All the operations are performed efficiently with the help of a ray representation.

The method is tested on different overhang features, including a lattice ball and a mushroom shape with a concave cap. All the supports generated for the examples can find their way to the build plate, which looks like they are escaping from the model. The computation time is around one second for these cases.

This is the first time truly realizing this “escaping” property in the generation of tree-like support structures. With this ET-Sup, it is expected that the AM industries can reduce the manufacturing lead time and save much labor work in post-processing.

Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.

To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.

Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.

The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.

The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.

The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.

The purpose of this paper is to report the design of a lightweight tree-shaped support structure for fused deposition modeling (FDM) three-dimensional (3D) printed models when the printing path is considered as a constraint.

A hybrid of genetic algorithm (GA) and particle swarm optimization (PSO) is proposed to address the topology optimization of the tree-shaped support structures, where GA optimizes the topologies of the trees and PSO optimizes the geometry of a fixed tree-topology. Creatively, this study transforms each tree into an approximate binary tree such that GA can be applied to evolve its topology efficiently. Unlike FEM-based methods, the growth of tree branches is based on a large set of FDM 3D printing experiments.

The hybrid of GA and PSO is effective in reducing the volume of the tree supports. It is shown that the results of the proposed method lead to up to 46.71% material savings in comparison with the state-of-the-art approaches.

The proposed approach requires a large number of printing experiments to determine the function of the yield length of a branch in terms of a set of critical parameters. For brevity, one can print a small set of tree branches (e.g. 30) on a single platform and evaluate the function, which can be used all the time after that. The steps of GA for topology optimization and those of PSO for geometry optimization are presented in detail.

The proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating complex models using the FDM technique. It can be adapted to the design of support structures for other additive manufacturing techniques such as Stereolithography and selective laser melting.

The purpose of this paper is to explore the possibility of combining additive manufacturing (AM) with topology optimization to generate support structures for addressing the challenging overhang problem. The overhang problem is considered as a constraint, and a novel algorithm based on continuum topology optimization is proposed.

A mathematical model is formulated, and the overhang constraint is embedded implicitly through a Heaviside function projection. The algorithm is based on the Solid Isotropic Material Penalization (SIMP) method, and the optimization problem is solved through sensitivity analysis.

The overhang problem of the support structures is fixed. The optimal topology of the support structures is developed from a mechanical perspective and remains stable as the material volume of support structures changes, which allows engineers to adjust the material volume to save cost and printing time and meanwhile ensure sufficient stiffness of the support structures. Three types of load conditions for practical application are considered. By discussing the uniform distributive load condition, a compromise result is achieved. By discussing the point load condition, the removal work of support structures after printing is alleviated. By discussing the most unfavorable load condition, the worst collapse situation of the printing model during printing process is sufficiently considered. Numerical examples show feasibility and effectiveness of the algorithm.

The proposed algorithm involves time-consuming finite element analysis and iterative solution, which increase the computation burden. Only the overhang constraint and the minimum compliance problem are discussed, while other constraints and objective functions may be of interest.

Compared with most of the existing heuristic or geometry-based support-generating algorithms, the proposed algorithm develops support structures for AM from a mechanical perspective, which is necessary for support structures particularly used in AM for mega-scale construction such as architectures and sculptures to ensure printing success and accuracy of the printed model.

With the rapid development of AM, complicated structures result from topology optimization are available for fabrication. The present paper demonstrates a combination of AM and topology optimization, which is the trend of fabricating manner in the future.

This paper remarks the first of attempts to use continuum topology optimization method to generate support structures for AM. The methodology used in this work is theoretically meaningful and conclusions drawn in this paper can be of important instruction value and practical significance.

Additive manufacturing based on arc welding is a fast and effective way to fabricate complex and irregular metal workpieces. Thin-wall metal structures are widely used in the industry. However, it is difficult to realize support-free freeform thin-wall structures. This paper aims to propose a new method of non-supporting thin-wall structure (NSTWS) manufacturing by gas metal arc welding (GMAW) with the help of a multi-degree of freedom robot arm.

This study uses the geodesic distance on the triangular mesh to build a scalar field, and then the equidistant iso-polylines are obtained, which are used as welding paths for thin-wall structures. Focusing on the possible problems of interference and the violent variation of the printing directions, this paper proposes two types of methods to partition the model mesh and generate new printable iso-polylines on the split meshes.

It is found that irregular thin-wall models such as an elbow, a vase or a transition structure can be deposited without any support and with a good surface quality after applying the methods.

The experiments producing irregular models illustrate the feasibility and effectiveness of the methods to fabricate NSTWSs, which could provide guidance to some industrial applications.

This study aims to develop a hierarchical topic analysis tool (HTAT) based on hierarchical Latent Dirichelet allocation (hLDA) to support digital humanities research that is associated with the need of topic exploration on the Digital Humanities Platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW). HTAT can assist humanities scholars on distant reading with analysis of hierarchical text topics, through classifying time-stamped texts into multiple historical eras, conducting hierarchical topic modeling (HTM) according to the texts from different eras and presenting through visualization. The comparative network diagram is another function provided to assist humanities scholars in comparing the difference in the topics they wish to explore and to track how the concept of a topic changes over time from a particular perspective. In addition, HTAT can also provide humanities scholars with the feature to view source texts, thus having high potential to be applied in promoting the effectiveness of topic exploration due to simultaneously integrating both the topic exploration functions of distant reading and close reading.

This study adopts a counterbalanced experimental design to examine whether there is significant differences in the effectiveness of topic inquiry, the number of relevant topics inquired and the time spent on them when research participants were alternately conducting text exploration using DHP-LCLW with HTAT or DHP-LCLW with Single-layer Topic Analysis Tool (SLTAT). A technology acceptance questionnaire and semi-structured interviews were also conducted to understand the research participants' perception and feelings toward using the two different tools to assist topic inquiry.

The experimental results show that DHP-LCLW with HTAT could better assist the research participants, in comparison with DHP-LCLW with SLTAT, to grasp the topic context of the texts from two particular perspectives assigned by this study within a short period. In addition, the results of the interviews revealed that DHP-LCLW with HTAT, in comparison with SLTAT, was able to provide a topic terms that better met research participnats' expectations and needs, and effectively guided them to the corresponding texts for close reading. In the analysis of technology acceptance and interview data, it can be found that the research participants have a high and positive tendency toward using DHP-LCLW with HTAT to assist topic inquiry.

The Jieba Chinese word segmentation system was used in the Mr. Lo Chia-Lun’s Writings Database in this study, to perform word segmentation on Mr. Lo Chia-Lun’s writing texts for topic modeling based on hLDA. Since Jieba word segmentation system is a lexicon based word segmentation system, it cannot identify new words that have still not been collected in the lexicon well. In this case, the correctness of word segmentation on the target texts will affect the results of hLDA topic modeling, and the effectiveness of HTAT in assisting humanities scholars for topic inquiry.

An HTAT was developed to support digital humanities research in this study. With HTAT, DHP-LCLW provides hmanities scholars with topic clues from different hierarchical perspectives for textual exploration, and with temporal and comparative network diagrams to assist humanities scholars in tracking the evolution of the topics of specific perspectives over time, to gain a more comprehensive understanding of the overall context of the texts.

In recent years, topic analysis technology that can automatically extract key topic information from a large amount of texts has been developed rapidly, but the topics generated from traditional topic analysis models like LDA (Latent Dirichelet allocation) make it difficult for users to understand the differences in the topics of texts with different hierarchical levels. Thus, this study proposes HTAT which uses hLDA to build a hierarchical topic tree with a tree-like structure without the need to define the number of topics in advance, enabling humanities scholars to quickly grasp the concept of textual topics and use different hierarchical perspectives for further textual exploration. At the same time, it also provides a combination function of temporal division and comparative network diagram to assist humanities scholars in exploring topics and their changes in different eras, which helps them discover more useful research clues or findings.

The aim of this study is to propose a method for assessing the service recovery performance of a manufacturing company with value‐added services. Service recovery performance is assessed by an index with value ranges from 0 to 100 percent.

A tree‐like structure was built to represent service recovery. This structure was weighted according to the degrees of each dimension's relative importance using the analytic hierarchy process (AHP) method. After construction, the dimensions were evaluated by considering how much they were applied during the process; the service recovery index and the gaps between importance and application were determined. The method was tested in a multinational manufacturing company and in two buyer companies.

It was possible to identify the most important service recovery dimensions from the perspective of a manufacturing company (“speed of recovery”, followed by “empowerment”) and the respective degree of application according to the buyers; the gaps between importance and application were determined, and a set of suggestions for the service recovery process was made.

The proposed method can be adapted for other companies, including those in other industries. Analysis of the degree of the application of the dimensions of recovery can be extended to other customers, which allows for the measurement of service recovery performance.

The recovery service is an organisational process relevant to manufacturing enterprises with value‐added services, which require measurement of their performance. The authors found no other references to a method that allows organisations to assess their performance in relation to recovery dimensions.

The purpose of this study is to evaluate the after-sales strategy of an industrial equipment manufacturer.

The research study’s object is the Brazilian operation of a company belonging to a multinational group that designs, manufactures and installs technology-based equipment. The research method is qualitative modeling with a quantitative analysis. A literature review and a focus group with managers organized the after-sales strategy of the company in four constructs measured by 24 indicators. The constructs are technical assistance (TA), reliability management (RM), customer relationships (CRs) and spare part logistics (SL). A total of seven managers evaluated the importance and performance of the indicators.

TA, RM and CRs are lagging constructs (the importance is greater than the performance), whereas SL is a leading construct (the opposite). The study proposed four strategic actions that change the type of emphasis that the company poses to service: from in-house to field maintenance service, from correction to prevention reliability improvement, from technical- to customer-focused relationships and from direct to integrated logistics service.

The study limits to the case of a technology-based manufacturing company.

The strategic movement reallocates resources from leading indicators to lagging indicators in a sharp, clear movement of forces in the company.

The main contribution is a structured method to evaluate and control the strategic performance of an industrial equipment manufacturer in after-sales activities.

Resource discovery in peer‐to‐peer (P2P) systems have been extensively studied. Unfortunately, most of the systems studied are not designed to take advantage of the heterogeneity in peer nodes. In this paper, we propose a novel P2P overlay called RATTAN, which serves as an underlay of a Gnutella‐like network. RATTAN exploits the heterogeneity of peer nodes by structuring capable nodes as the core of the overlay. Using a tree‐like structure, RATTAN can maximize the search scope with a minimal number of query messages. We evaluate RATTAN with simulation. The experiments show the following interesting results. First, RATTAN is robust by exploiting redundant overlay links. Second, the maximum bandwidth demand for processing the protocol of a single RATTAN overlay is nearly 1M bits/sec. However, around 80% of the nodes merely take 66 bits/sec. One implication is that we can use a small number of relatively capable peers (e.g., stable machines with a 100M bits/sec network interface) to process the 1M bits/sec protocol overhead and serve other peers that only need to spend 66 bits/sec for processing protocol overhead.

A programme to simulate part flow in assembly automation, SIMAS, has been developed with support from Swiss industry. It allows the user to optimise investment as well as preview system behaviour.