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During the 3D printing process, the model needs to add a support structure to ensure structural stability. Excessive support structure reduces printing efficiency and results in material cost. A flexible support platform for 3 D printing has been designed. It can form an external support structure to replace the original support structure. This paper aims to study the influence of a model’s build orientation on properties when the model is printed on the platform, aiming to provide users with suitable solutions.

A fitness function for estimating the support structure with a support length is constructed. The particle swarm optimization (PSO) algorithm is modified and applied to find the build orientation that minimizes the support structure. However, when the model is printed on the platform, the build orientation of the minimum support structure enhances the complexity of the working path, resulting in an increase of printing time, which needs to be avoided. This paper applies a multi-objective particle swarm optimization (MOPSO) algorithm to minimize the support structure while minimizing printing time. The Pareto solution is obtained by the algorithm.

It is found that the model that has the cantilever structure can reduce more support structure after optimization on the platform, when there is surface quality requirement. When there is no limit, the modified algorithm can minimize the support structure of each model. Considering support structure and printing time, the MOPSO algorithm can easily get optimization results to guide the practical work.

This paper optimizes the model’s build orientation on the flexible support platform by PSO, thereby reducing material cost and improving work efficiency.

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.

Selective laser melting (SLM) enables the fabrication of lightweight and complex metallic structures. Support structures are required in the SLM process to successfully produce parts. Supports are typically lattice structures, which cost much time and material to manufacture. Besides, the manufacturability of these supports is undesirable, which may impact the quality of parts or even fail the process. The purpose of this paper is to investigate the efficiency and mechanical properties of advanced internal branch support structures for SLM.

The theoretic weight of a branch support and a lattice support of the same plane were calculated and compared. A group of standard candidates of branch support structures were manufactured by SLM. The weight and scanning time of specimens with different design parameters were compared. Then, these samples were tested using an MTS Insight 30 compression testing machine to study the influence of different support parameters on mechanical strength of the support structures.

The results show that branch type supports can save material, energy and time used needed for their construction. The yield strength of the branch increases with the branch diameter and inclined branch angle in general. Furthermore, branch supports have a higher strength than traditional lattice supports.

To the best of the authors’ knowledge, this is the first work investigating production efficiency and mechanical properties of branch support structures for SLM. The findings in this work are valuable for development of advanced optimal designs of efficient support structures for SLM process.

The purpose of this paper is to design a lightweight tree-shaped internal support structure for fused deposition modeling (FDM) three-dimensional (3D) printed shell models.

A hybrid of an improved particle swarm optimization (PSO) and greedy strategy is proposed to address the topology optimization of the tree-shaped support structures, where the improved PSO is different from traditional PSO by integrating the best component of different particles into the global best particle. In addition, different from FEM-based methods, the growing of tree branches is based on a large set of FDM 3D printing experiments.

The proposed improved PSO and its combination with a greedy strategy is effective in reducing the volume of the tree-shaped support structures. Through comparison experiments, it is shown that the results of the proposed method outperform the results of recent works.

The proposed approach requires the derivation of the function of the yield length of a branch in terms of a set of critical parameters (printing speed, layer thickness, materials, etc.), which is to be used in growing the tree branches. This process requires a large number of printing experiments. To speed up this process, the users can print a dozen of branches on a single build platform. Thereafter, the users can always use the function for the fabrication of the 3D models.

The proposed approach is useful for the designers and manufacturers to save materials and printing time in fabricating the shell models using the FDM technique; although the target is to minimize the volume of internal support structures, it is also applicable to the exterior support structures, and it can be adapted to the design of the tree-shaped support structures for other AM techniques such as SLA and SLM.

This study aims to further the understanding of support structures and the likely impacts on maraging steel MS1 parts fabricated by selective laser melting (SLM) at 45°, 60° and 75° building angles.

Two groups of samples, one group with support structures and the other group without support structures, were designed with the same specifications and printed under the same conditions by SLM at 45°, 60° and 75° building angles. Differences in dimensional accuracy, surface roughness, Vickers microhardness, residual stress and microstructure were compared between groups.

The results showed that with support structures, more accurate dimension and slightly higher Vickers microhardness could be obtained. Larger compressive stress dominated and was more uniformly distributed on the supporting surface. Without support structures, the dimension became more precise as the building angle increased and alternating compressive and tensile stress was unevenly distributed on the supporting surface. In addition, the surface roughness of the outer surface decreased with the increase of the built angle, regardless of the support structures. Furthermore, whether the building angle was 45°, 60° or 75°, the observed microstructures revealed that the support structures altered the orientation of the molten pool and the direction of grain growth.

This paper studies the influence of support structures on the workpieces printed at different building angles. Support structures affect the residual stress distribution, heat dissipation rate and microstructure of the parts, and thus affecting the printing quality. Therefore, it is necessary to balance the support strategy and printing quality to better apply or design the support structures in SLM.

Support structures used in laser powder bed fusion are often difficult to clean from unsintered powder at the end of the process. This issue can be significantly reduced through a proper design of these auxiliary structures. This paper aims to investigate preliminary the airflow within differently oriented support structures and to provide design guidelines to enhance their cleanability, especially the depowdering of them.

This study investigates the cleanability of support structures in powder bed fusion technology. Digital models of cleaning operations were designed through computer-aided engineering systems. Simulations of the airflow running into the powder entrapped within the thin walls of auxiliary supports were implemented by computational fluid dynamics. This approach was applied to a set of randomly generated geometrical configurations to determine the air turbulence intensity depending on their design.

The results, which are based on the assumption that a relationship exists between turbulence and powder removal effectiveness, demonstrated that the maximum cleanability is obtainable through specific relative rotations between consecutive support structures. Furthermore, it was possible to highlight the considerable influence of the auxiliary structures next to the fluid inlet. These relevant findings establish optimal design rules for the cleanability of parts manufactured by powder bed fusion processes.

This study presents a preliminary investigation into the cleanability of support structures in laser powder bed fusion, which has not been addressed by previous literature. The results allow for a better understanding of the fluid dynamics during cleaning operations. New guidelines to enhance the cleanability of support structures are provided based on the results of simulations.

The aim of this chapter is to describe a four-type model of organisational structures and to discuss two cases, Embrapa and the Brazilian Agricultural Research Corporation, as well as additional cases at SAM-Research and the centre for shared medical support services established at the University of Bologna.

These cases should help readers understand the importance of designing distinctive, tailored-made support services while keeping these structures flexible for further adaptation under unforeseen changes.

The chapter concludes by stressing the role of institutions to steadily invest in the design of these tailored support structures and in personalised training for their support staff.

For an organization to realize the intended benefits of an enternprise resource planning (ERP) investment, it must integrate both technical expertise and functional area knowledge, and it must have continuing support after implementation. The study aims to expand understanding of how organizations ensure the necessary support from functional experts during and after ERP installations. In particular, the study aims to address the question of the type of horizontal support mechanism chosen for this support and how managers make these choices.

The study is a replicated case study based on interviews with project leaders in nine universities judged to have successful PeopleSoft ERP implementations. Thematic analysis is applied to identify the factors influencing managerial choices and organizational decisions made to assure post‐implementation ERP support.

The findings indicate that managers of ERP implementations recognize the necessity for horizontal coordinating mechanisms both during and after implementation. The paper finds no single “best” structure in the cases, nor does it observe that the support structure decision is always based on a deliberate organizational strategy. The findings indicate that selection of post‐implementation support structure is often a negotiated outcome. Ultimately, the paper finds that the outcomes were based on three factors: the situated context of the original implementation project goals; the nature of early commitments made to functional subject matter experts and their departments; and the initial project structure used during the implementation phase.

This research fills a gap in research on ERP support structures by examining how localized organizations assure the necessary support from subject matter experts, commencing with project inception and continuing through post‐implementation. The results contribute to theory by illustrating the value of a process‐based approach to understanding the factors that affect the choice of support structures. The findings contribute to practice by highlighting how early management decisions and the methods executives chose to assure commitments from key stakeholders can restrict the range of options for post‐implementation organizational structures.

High-rise tower structures supported by side frame structure and viscous damper in chemical industry can produce plasticity under dynamic loads, such as wind and earthquake, which will heavily influence the long-term safety operation. This paper aims to systematically study the optimization design of these structures by free vibration and dynamic shakedown analysis.

The transfer matrix method and Euler–Bernoulli beam vibration are used to study the free vibration characteristic of the simplified high-rise tower structure. Then the extended stress compensation method is used to construct the self-equilibrated stress by using the dynamic load vertexes and the lower bound dynamic shakedown analysis for the structure with viscous damper. Using the proposed method, comprehensive parametric studies and optimization are performed to examine the shakedown load of high-rise tower with various supported conditions.

The numerical results show that the supported frame stiffness, attached damper or spring parameters influence the free vibration and shakedown characters of high-rise tower very much. The dynamic shakedown load is lowered down quickly with external load frequency increasing to the fundamental natural frequency of the structure under spring supported condition, while changed little with the damping connection. The optimized location and parameter of support are obtained under dynamical excitations.

In this study, the high-rise tower structure is simplified as a cantilever beam supported by a short cantilever beam and a damper under repeated dynamic load, and linear elasticity for solid is assumed for free vibration analysis. The current analysis does not account for effects such as large deformation, stochastic external load and nonlinear vibration conditions which will inevitably be encountered and affect the load capacity.

This study provides a comprehensive method for the dynamical optimization of high-rise tower structure by combining free vibration and shakedown analysis.

Increasingly 3D printing is used for parts of garments or for making whole garments due to their flexibility and comfort and for functionalizing or enhancing the aesthetics of the final garment and hence adding value. Many of these applications rely on complex programming of the 3D printer and are usually provided by the vendor company. This paper introduces a simpler, easier platform for designing 3D-printed textiles, garments and other artifacts, by predicting the optimal orientation of the target objects to minimize the use of plastic filaments.

The main idea is based on the shadow-casting analogy, which assumes that the volume of the support structure is similar to that of the shadow from virtual sunlight. The triangular elements of the target object are converted into 3D pixels with integer-based normal vectors and real-numbered coordinates via vertically sparse voxelization. The pixels are classified into several groups and their noise is suppressed using a specially designed noise-filtering algorithm called slot pairing. The final support structure volume information was rendered as a two-dimensional (2D) figure, similar to a medical X-ray image. Thus, the authors named their method modified support structure tomography.

The study algorithm showed an error range of no more than 1.6% with exact volumes and 6.8% with slicing software. Moreover, the calculation time is only several minutes for tens of thousands of mesh triangles. The algorithm was verified for several meshes, including the cone, sphere, Stanford bunny and human manikin.

Simple hardware, such as a CPU, embedded system, Arduino or Raspberry Pi, can be used. This requires much less computational resources compared with the conventional g-code generation. Also, the global and local support structure is represented both quantitatively and graphically via tomographs.