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The purpose of this study is to investigate the manufacturability of Fe-3Si lattice structures and the resulting mechanical properties. This study could lead to the successful processing of squirrel cage conductors (a lattice structure by design) of an induction motor by additive manufacturing in the future.

The compression behaviour of two lattice structures where struts are arranged in a face-centred cubic position and vertical edges (FCCZ), and struts are placed at body-centred cubic (BCC) positions, prepared by laser powder bed fusion (LPBF), is explored. The experimental investigations are supported by finite element method (FEM) simulations.

The FCCZ lattice structure presents a peak in the stress-strain curve, whereas the BCC lattice structure manifests a plateau. The vertical struts aligned along the compression direction lead to a significant increase in the load-carrying ability of FCCZ lattice structures compared to BCC lattice structures. This results in a peak in the stress-strain curve. However, the BCC lattice structure presents the bending of struts with diagonal struts carrying the major loads with struts near the faceplate receiving the least load. A high concentration of geometrically necessary dislocations (GNDs) near the grain boundaries along cell formation is observed in the microstructure.

To the best of the authors’ knowledge, this is the first study on additive manufacturing of Fe-3Si lattice structures. Currently, there are no investigations in the literature on the manufacturability and mechanical properties of Fe-3Si lattice structures.

This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

Demanding applications could benefit from the mathematical parametrization of lattice structures as this could lead not only to the characterization of structure–property relation but also facilitates the tailoring of the effective mechanical properties. This paper aims to characterize the mechanical performance of sine-based lattices. The characterization includes the results of in-plane Poisson’s ratio plates models, and the stiffness of additively manufactured lattice plates when loaded in the out-of-plane direction, with the objective of obtaining a relation with their geometrical parameters.

The geometrical parameter–Poisson’s ratio relationship was characterized via finite element (FE) simulations. The stiffness was also measured on additively manufactured polylactic acid lattice plates and contrasted with FE computations.

The characterization of auxetic lattice plates performed using in-plane and out-of-plane loading leads to key properties when deciding the geometry specific for applications: relative density, auxetic behavior and stiffness. Approximately 26% reduction of stiffness was observed between the square lattice and sine-based lattices of the same volume fraction.

Auxetic metamaterials are potential candidates for applications in biomedical engineering, smart sensors, sports and soft robotics. This paper aims to contribute to the existing gap in the study of auxetic metamaterials subjected to complex loading conditions, other than simple tension and compression, required for the mentioned applications.

Additive Manufacturing (AM) conventionally necessitates an intermediary slicing procedure using the standard tessellation language (STL) data, which can be computationally burdensome, especially for intricate microcellular architectures. This study aims to propose a direct slicing method tailored for digital light processing-type AM processes for the efficient generation of slicing data for microcellular structures.

The authors proposed a direct slicing method designed for microcellular structures, encompassing micro-lattice and triply periodic minimal surface (TPMS) structures. The sliced data of these structures were represented mathematically and then convert into 2D monochromatic images, bypassing the time-consuming slicing procedures required by 3D STL data. The efficiency of the proposed method was validated through data preparations for lattice-based nasopharyngeal swabs and TPMS-based ellipsoid components. Furthermore, its adaptability was highlighted by incorporating 2D images of additional features, eliminating the requirement for complex 3D Boolean operations.

The direct slicing method offered significant benefits upon implementation for microcellular structures. For lattice-based nasopharyngeal swabs, it reduced data size by a factor of 1/300 and data preparation time by a factor of 1/8. Similarly, for TPMS-based ellipsoid components, it reduced data size by a factor of 1/60 and preparation time by a factor of 1/16.

The direct slicing method allows for bypasses the computational burdens associated with traditional indirect slicing from 3D STL data, by directly translating complex cellular structures into 2D sliced images. This method not only reduces data volume and processing time significantly but also demonstrates the versatility of sliced data preparation by integrating supplementary features using 2D operations.

Additive manufacturing (AM), a rapidly evolving paradigm, has shown significant advantages over traditional subtractive processing routines by allowing for the custom creation of structural components with enhanced performance. Numerous studies have shown that the technical qualities of AM components are profoundly affected by the discovery of novel metastable substructures in diverse alloys. Therefore, the purpose of this study is to determine the effect of cell structure parameters on its mechanical response.

Initially, a methodology was suggested for testing porous materials, focusing on static tensile testing. For a qualitative evaluation of the cellular structures produced, computed tomography (CT) was used. Then, the CT scanner was used to analyze a sample and determine its actual relative density, as well as perform a detailed geometric analysis.

The experimental research demonstrates that the mechanical properties of a cell’s structure are significantly influenced by its shape during formation. It was also determined that using selective laser melting to produce cell structures with a minimum single-cell size of approximately 2 mm would be the most appropriate method.

Further studies of cellular structures for testing their static tensile strength are planned for the future. The study will be carried out for a larger number of samples, taking into account a wider range of cellular structure parameters. An important step will also be the verification of the results of the static tensile test using numerical analysis for the model obtained by CT scanning.

The fabrication of metallic parts with different cellular structures is very important with a selective laser melted machine. However, the determination of cell size and structure with mechanical properties is quiet novel in this current investigation.

The present study investigates the mechanical properties of three types of Ti6Al4V ELI bone screws realized using the laser powder bed fusion (LPBF) process: a fully threaded screw and two groups containing differently arranged sectors made of lattice-based Voronoi (LBV) structure in a longitudinal and transversal position, respectively. This study aims to explore the potentialities related to the introduction of LBV structure and assess its impact on the implant’s primary stability and mechanical performance.

The optimized bone screw designs were realized using the LPBF process. The quality and integrity of the specimens were assessed by scanning electron microscopy and micro-computed tomography. Primary stability was experimentally verified by the insertion and removal of the screws in standard polyurethane foam blocks. Finally, torsional tests were carried out to compare and assess the mechanical strength of the different designs.

The introduction of the LBV structure decreases the elastic modulus of the implant. Longitudinal LBV type screws demonstrated the lowest insertion torque (associated with lower bone damage) while still displaying promising torsional strength and removal force compared with full-thread screws. The use of LBV structure can promote improved functional performances with respect to the reference thread, enabling the use of lattice structures in the biomedical sector.

The paper fulfils an identified interest in designing customized implants with improved primary stability and promising features for secondary stability.

The tender documents, an essential data source for internet-based logistics tendering platforms, incorporate massive fine-grained data, ranging from information on tenderee, shipping location and shipping items. Automated information extraction in this area is, however, under-researched, making the extraction process a time- and effort-consuming one. For Chinese logistics tender entities, in particular, existing named entity recognition (NER) solutions are mostly unsuitable as they involve domain-specific terminologies and possess different semantic features.

To tackle this problem, a novel lattice long short-term memory (LSTM) model, combining a variant contextual feature representation and a conditional random field (CRF) layer, is proposed in this paper for identifying valuable entities from logistic tender documents. Instead of traditional word embedding, the proposed model uses the pretrained Bidirectional Encoder Representations from Transformers (BERT) model as input to augment the contextual feature representation. Subsequently, with the Lattice-LSTM model, the information of characters and words is effectively utilized to avoid error segmentation.

The proposed model is then verified by the Chinese logistic tender named entity corpus. Moreover, the results suggest that the proposed model excels in the logistics tender corpus over other mainstream NER models. The proposed model underpins the automatic extraction of logistics tender information, enabling logistic companies to perceive the ever-changing market trends and make far-sighted logistic decisions.

(1) A practical model for logistic tender NER is proposed in the manuscript. By employing and fine-tuning BERT into the downstream task with a small amount of data, the experiment results show that the model has a better performance than other existing models. This is the first study, to the best of the authors' knowledge, to extract named entities from Chinese logistic tender documents. (2) A real logistic tender corpus for practical use is constructed and a program of the model for online-processing real logistic tender documents is developed in this work. The authors believe that the model will facilitate logistic companies in converting unstructured documents to structured data and further perceive the ever-changing market trends to make far-sighted logistic decisions.

The purpose of this article covers the design and manufacture of porous materials that can be used in different engineering applications by additive manufacturing.

The most important design parameters of the porous materials are the cell structure and wall thickness. These two design criteria are difficult to control in porous materials produced by conventional production methods. In the study, two different wall thicknesses and four different pore diameters of the porous structure were determined as design parameters.

A compression test was applied to the produced samples. Also, the densities of the produced samples were compared. As a result of the study, changes in mechanical properties were observed according to the cell wall thickness and pore size.

The originality of the study is that, unlike traditional porous structure production, the pore structure and cell wall thicknesses can be produced in desired dimensions. In addition, a closed pore structure was tried to be produced in the study. Studies in the literature generally have a tube-type pore structure.

Numerous metals can be processed using the additive manufacturing process laser-based powder bed fusion of metals (PBF-LB/M, ISO/ASTM 52900). The main advantages of additive manufacturing technologies are the high degree of design freedom and the cost-effective implementation of lightweight structures. This could be profitable for gears with increased power density, combining reduced mass with considerable material strength. Current research on additively manufactured gears is focused on developing lightweight structures but is seldom accompanied by simulations and even less by mechanical testing. There has been very little research into the mechanical and material properties of additively manufactured gears. The purpose of this study is to investigate the behavior of lightweight structures in additively manufactured gears under static loads.

This research identifies the static load-carrying capacity of helical gears with different lightweight structures produced by PBF-LB/M with the case hardening steel 16MnCr5. A static gear loading test rig with a maximum torque at the pinion of T₁ = 1200 Nm is used. Further focus is set on analyzing material properties such as the relative density, microstructure, hardness depth profile and chemical composition.

All additively manufactured gear variants show no failure or plastic deformation at the maximum test load. The shaft hub connection, the lightweight hub designs and the gearing itself are stable and intact regarding their form and function. The identified material characteristics are comparable to conventionally manufactured gears (wrought and machined), but also some particularities were observed.

This research demonstrates the mechanical strength of lightweight structures in gears. Future research needs to consider the dynamic load-carrying capacity of additively manufactured gears.

This paper aims to propose a new framework on prioritizing and deployment of design for additive manufacturing (DfAM) strategies to an industrial component using Fuzzy TOPSIS multiple criteria decision-making (MCDM) techniques. The proposed framework is then applied to an automotive component, and the results are discussed and compared with existing design.

Eight DfAM design alternatives associated with eight design criteria have been identified for framing new DfAM strategies. The prioritization order of the design alternatives is identified by Fuzzy TOPSIS MCDM technique through its closeness coefficient. Based on Fuzzy TOPSIS MCDM output, each of the design alternatives is applied sequentially to an automobile component as a case study. Redesign is carried out at each stage of DfAM implementation without affecting the functionality.

On successful implementation of proposed framework to an automotive component, the mass is reduced by 43.84%, from 0.429 kg to 0.241 kg. The redesign is validated by finite element analysis, where von Mises stress is less than the yield stress of the material.

The proposed DfAM framework and strategies will be useful to designers, R&D engineers, industrial practitioners, experts and consultants for implementing DfAM strategies on any industrial component without impacting its functionality.

To the best of the authors’ knowledge, the idea of prioritization and implementation of DfAM strategies to an automotive component is the original contribution.