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This paper aims to propose an analytical thermal three-dimensional model that allows an efficient evaluation of the thermal effect of the laser-scanning path. During manufacturing by laser powder bed fusion (LPBF), the laser-scanning path influences the thermo-mechanical behavior of parts. Therefore, it is necessary to validate the path generation considering the thermal behavior induced by this process to improve the quality of parts.

The proposed model, based on the effect of successive thermal flashes along the scanning path, is calibrated and validated by comparison with thermal results obtained by FEM software and experimental measurements. A numerical investigation is performed to compare different scanning path strategies on the Ti6Al4V material with different stimulation parameters.

The simulation results confirm the effectiveness of the approach to simulate the thermal field to validate the scanning strategy. It suggests a change in the scale of simulation thanks to high-performance computing resources.

The flash-based approach is designed to ensure the quality of the simulated thermal field while minimizing the computational cost.

This paper aims to improve the infilling efficiency and the quality of parts forming. It proposes two improved scanning path planning algorithm based on velocity orthogonal decomposition.

The algorithms this paper proposes replace empty paths and corners with circular segments, driving each axis synchronously according to the SIN or COS velocity curve to make the extruder always moves at a constant speed at maximum during the infilling process. Also, to support the improved algorithms, a three-dimensional (3D) printing control system based on circular motion controller is also designed.

The simulation and experiment results show that the improved algorithms are effective, and the printing time is shortened more significantly, especially in the case of small or complex models. What’s more, the optimized algorithm is not only compact in shape but also not obvious in edge warping.

The algorithms in this paper are not applicable to traditional motion controllers.

The algorithms in this paper improve the infilling efficiency and the quality of parts forming.

There are no social implications in this paper.

The specific optimization method of parallel-line scanning algorithm based on velocity orthogonal decomposition is replacing the empty paths with arc corners. And the specific optimization method of contour offsetting algorithm based on velocity orthogonal decomposition is to add connection paths between adjacent contours and turn all straight corners into arcs. What’s more, the 3D printing control system based on the circular motion controller can achieve multi-axis parallel motion to support these two improved path scanning algorithms.

In Laser Power Bed Fusion (LPBF), the process and operating parameters influence the mechanical and geometrical characteristics of the manufactured parts. Therefore, the optimization and control of these parameters are mandatory to improve the quality of the produced parts. During manufacturing, the process parameters are usually constant whatever the part size or the built layer. With such settings, the manufacturing process may lead to an inhomogeneous thermal behavior and locally overheating areas, impacting the part quality. The aim of this study is to take advantage of an analytical thermal model to modulate the laser power upstream of manufacturing.

The approach takes place in two steps: the first step consists in calculating the preheating temperature at the considered point and the second one determines the power modulation of the laser to reach the desired temperature at this point.

Numerical investigations on several use cases show the effectiveness of the method to control the overheated areas and to homogenize the simulated temperature distribution.

The specificity of this model lies in its ability to directly calculate the amount of energy to be supplied without any iterative calculation. Furthermore, to be as close as possible to the technology used on LPBF machines, the kinematic behavior of the scanning head and the laser response time are also integrated into the calculation.

The purpose of this paper is to correct the beam deflection errors and beam defocus by using a digital scanning system. Electron beam selective melting (EBSM) is an additive manufacturing technology for metal parts. Beam deflection errors and beam defocus at large deflection angles would greatly influence the accuracy of the built parts.

The 200 × 200 mm2 scanning area of the electron beam is discretized into 1001 × 1001 points arranged in array, based on which a digital scanning system is developed. To correct the deflection errors, the electron beam scans a 41 × 41 testing grid, and the corrective algorithm is based on the bilinear transformation from the grid points’ nominal coordinates to their measured coordinates. The beam defocus is corrected by a dynamic focusing method. A three-dimensional testing part is built with and without using the corrective algorithm, and their accuracies are quantitatively compared.

The testing grid scanning result shows that the accuracy of the corrected beam deflection system is better than ± 0.2 mm and beam defocus at large deflection angles is eliminated visibly. The testing part built with using the corrective algorithm is of greater accuracy than the one built without using it.

Benefiting from the digital beam control method, the model-to-part accuracy of the system is effectively improved. The digital scanning system is feasible in rapid manufacturing large and complex three-dimensional metal parts.

The purpose of this paper is to investigate the research approach to optimize shape accuracy, dimensional accuracy and density of customized orthodontic production fabricated by selective laser melting (SLM).

A series of process experiments were applied to fabricating customized brackets directly by SLM, using 316L stainless steel. Shape accuracy can be optimized through the study on fabricating characteristics of non‐support overhanging structure. A scanning strategy combining contour scanning with orthogonal scanning, which differ in scanning speed and spot compensations, was proposed to improve dimensional accuracy. Scanning laser surface re‐melting was added to enhance the SLM density.

Optimized SLM parameters lead to high shape precision of customized brackets, and the average size error of bracket slot is less than 10 μm. The customized brackets density is more than 99 per cent, and the surface quality and mechanical properties meet the requirements.

The paper presents the state of the art in SLM of customized production (especially medical appliances) by optimizing part properties. It is the first time that SLM is employed in the manufacturing of customized orthodontic products. It shows the original research on overhanging structure and compound scanning strategy, approach to optimize SLM part accuracy. An improved laser surface re‐melting is employed in the density optimization.

The traditional vision system cannot automatically adjust the feature point extraction method according to the type of welding seam. In addition, the robot cannot self-correct the laying position error or machining error. To solve this problem, this paper aims to propose a hierarchical visual model to achieve automatic arc welding guidance.

The hierarchical visual model proposed in this paper is divided into two layers: welding seam classification layer and feature point extraction layer. In the welding seam classification layer, the SegNet network model is trained to identify the welding seam type, and the prediction mask is obtained to segment the corresponding point clouds. In the feature point extraction layer, the scanning path is determined by the point cloud obtained from the upper layer to correct laying position error. The feature points extraction method is automatically determined to correct machining error based on the type of welding seam. Furthermore, the corresponding specific method to extract the feature points for each type of welding seam is proposed. The proposed visual model is experimentally validated, and the feature points extraction results as well as seam tracking error are finally analyzed.

The experimental results show that the algorithm can well accomplish welding seam classification, feature points extraction and seam tracking with high precision. The prediction mask accuracy is above 90% for three types of welding seam. The proposed feature points extraction method for each type of welding seam can achieve sub-pixel feature extraction. For the three types of welding seam, the maximum seam tracking error is 0.33–0.41 mm, and the average seam tracking error is 0.11–0.22 mm.

The main innovation of this paper is that a hierarchical visual model for robotic arc welding is proposed, which is suitable for various types of welding seam. The proposed visual model well achieves welding seam classification, feature point extraction and error correction, which improves the automation level of robot welding.

To present a Mobile Scanning System for digitizing three‐dimensional (3D) models of real‐world terrain.

A combination of sensors (video, laser range, positioning, orientation) is placed on a mobile platform, which moves past the scene to be digitized. Data fusion from the sensors is performed to construct an accurate 3D model of the target environment.

The developed system can acquire accurate models of real‐world environments in real time, at resolutions suitable for a variety of tasks.

Treating the individual subsystems of the mobile scanning system independently yields a robust system that can be easily reconfigured on the fly for a variety of scanning scenarios.

Selective laser melting (SLM) is increasingly used to manufacture bone implants from titanium alloys with particular interest in porous lattice structures. These complex constructs have been shown to be capable of matching native bone mechanical behaviour leading to improved osseointegration while providing numerous clinical advantages, encouraging their broad use in medical devices. However, producing lattices with a strut diameter similar in scale to a typical SLM melt pool or using the same process parameters and scan strategies intended for bulk solid components may lead to geometric inaccuracies. The purpose of this study is to evaluate and optimise the single contour strategy for the production of Ti-6Al-4V lattices.

Herein, the potential of an unfilled single contour (SC) scanning strategy to improve the reproducibility of porous lattices when compared with a single contour and fill approach (SC + F) is explored. For this purpose, two parametric analysis were carried out on Ti-6Al-4V diamond unit cell lattices with different strut sizes and scan strategies. Porosity and accuracy measurements were correlated with processing parameters and printing strategy to provide the optimal processing window for lattice manufacturing.

SC is shown to be a viable strategy for production of Ti-6Al-4V lattices with a strut diameter below 350 µm. Parametric analysis highlights the limits of this method in producing fully dense struts with energy density presented as a useful practical tool to guide some aspects of parameter selection (design strut diameter achieved at approximately 0.1 J/mm in this study). Finally, a process map combining data from both parametric studies is provided to guide, predict and control lattice strut geometry and porosity obtained using the SC strategy.

These results explore the use of non-standard SC scanning strategy as a viable method for producing strut-based lattice structures and compare against the traditional contour and fill approach (SC + F).

The purpose of this study is to establish a finite element (FE) model with the random distribution of the Nylon12/hydroxyapatite (PA12/HA) composite material in selective laser sintering (SLS) process for considering the material anisotropy, which aims to obtain the law of temperature and stress changes in PA12/HA sintering.

By using python script in Abaqus, the FE model is established in which the two materials are randomly distributed and are assigned to their intrinsic temperature-dependent physical parameters. Molten pool sizes at various process parameters were evaluated in terms of numerical simulation and scanning electron microscope analysis, identifying a good agreement between them. Evaluation of temperature and stress distribution under the condition of different HA contents was also conducted.

It shows that the uneven distribution and quantity of HA powder play a vital role in stress concentration and temperature increase. Additionally, the influence of HA addition on the mechanical performance of SLS-fabricated parts shows that it is conducive to improve compressive strength when the HA ratio is less than 5% because an excess of HA powder tends to bring about a certain amount of microspores resulting in a decrease in part density.

The FE model of the PA12/HA composite material with parameterized random distribution in SLS can be applied in other similar additive manufacturing technologies. It provides a feasible guideline for the numerical analysis of properties of composite materials.

Boisot’s I‐space is used as a framework to explain the comparative success of computer‐based tools in information scanning and dissemi‐ nation, and the failure to support problem areas in the process of knowledge creation, especially where this involves interactions within user groups. Recent research indicates that process‐based studies are likely to be productive, and that there is a useful overlap between information science and computer science interests and methods.