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Explainable artificial intelligence method is used to understand the underlying phenomenon of the machine learning (ML) algorithm prediction. In this work, a powerful XAI technique, SHapley Additive exPlanations (SHAP) is implemented by inputting the trained XGBregressor ML model. The following 3D printing process parameters, layer thickness, wall thickness, infill density, infill pattern, nozzle temperature, bed temperature, print speed, material, fan speed are considered to predict the tensile strength, roughness and elongation. SHAP explanations clarify process parameters’ proportional and cumulative effects on anticipated qualities. The XGBoost model achieved a mean squared error (MSE) of 0.591 and root mean squared error (RMSE) of 0.769. SHAP visualization plots are presented to understand the patterns of interaction between the most influential process parameters. The plots revealed that layer height positively correlates with roughness, while nozzle temperature is the most influential factor for tensile strength. Infill density is key for elongation, with higher infill leading to higher predicted elongation. This knowledge can be used to prioritize parameter optimization and control for achieving desired material properties, ultimately leading to more reliable and consistent 3D printing processes.

In the era of Industry 4.0, 3D printing has shown significant outcomes. To address the challenges of large-format complex material printing and forming, such as spatial constraints and excessive support structures in traditional 3D printing, the integration of industrial robots with 3D printing technology is proposed. However, robotic 3D printing introduces challenges in path planning and real-time optimization. This paper presents a methodology for path planning and real-time optimization of robotic arms on a 3D printing platform. The approach involves adjusting the printing path by modifying the nozzle printing posture and implementing obstacle avoidance algorithms. The study uses geometric and algebraic methods to optimize the robotic arm trajectory to improve the precision of reaching print points, reduce the printing cycle, and minimize material wastage. To verify the feasibility of this method, a case study in 3D printing is conducted to examine the practical application of motion planning for robotic arms based on digital twin technology.

Three-dimensional (3D) printing has bought much enthusiasm for medical applications. The upgraded quality with the use of 3D printing has gained detailed clinical and associated results. This paper bridges the available writing, based on literature, about the capability of 3D printing innovation in medical applications. 3D printing can build highly complex individualized medical parts/tools/inserts, etc., with improved results and increments financial plausibility. This innovative approach offers a potential level of openness that is fundamental for remote and asset restricted areas where human services are frequently constrained. The 3D printing-based advances immensely affect the reproduction of terrible wounds, facial and appendage prosthetic improvement, and headways in biologic and manufactured inserts. It is identified from the available literature that 3D printing is being incorporated successfully in medical cases for improved medical results. Its applications fluctuate from anatomical models for study/training purposes to fully functional implantable body parts/organs.

With the development of inkjet-/3D-/4D-printing additive manufacturing technologies, flexible 3D substrate with complex structures can be patterned with dielectric, conductive and semi-conductive materials to realize novel RF designs. This paper provides a review of state-of-the-art additively manufactured passive RF devices including antennas and frequency selective surfaces (FSS), couplers, where origami-inspired structure enables unprecedented capabilities of on-demand continuous frequency tunability and deployability. This paper also discusses additively manufactured active RF modules and systems such as inkjet printed RF energy harvester system with high sensitivity and efficiency for Internet of Things (IoT), smart cities and wireless sensor networks (WSN) applications, inkjet-printed RF front ends, and inkjet-printed mm-wave backscatter modules.

The recent developments in mmWave and Internet of Things (IoT) technologies have dramatically increased the interest and demand for radio frequency (RF) devices that can be used for applications such as smart cities, energy harvesting, and ubiquitous wireless sensor networks. Additive manufacturing technologies (AMT) plays an important role to support these applications, as they allows to significantly reduce fabrication costs and times while enabling the achievement of devices with more complex geometries and the possibility of using a wide variety of materials. This publication reviews recent developments of state-of-the-art wireless devices including reconfigurable antennas, frequency-selective surfaces and highly scalable phased arrays enabled by AMT capabilities. It also discusses the benefits of AMT in the fabrication of interconnects that are suitable for packaging of fully-integrated antennas.

This review encompasses additive manufacturing techniques for crafting 5G electronics, showcasing how these methods innovate device creation with novel examples. A wearable phased array device on commonplace 3D printed material is described, with integrated microfluidic cooling channels used for thermal regulation of integrated circuit bulk components. Mechanical and electrical tunability are exemplified in an origami-inspired phased array structure. A 3D printed IoT cube structure shows the flexibility in the number of geometries additively manufactured 5G devices can adhere to. Finally, integrating 3D optical lenses with 5G electronics is shown.

Traditionally, firms often run independent promotional activities to attract consumers and improve their competitiveness. With the rapid development of three-dimensional (3D) printing, also known as additive manufacturing, a growing number of firms in different markets cooperate to conduct cooperative promotion to meet consumer demand. Different from independent promotion, which means that firms promote their products through their individual promotional activities, when they carry out cooperative promotion, in addition to their individual promotional activities, they also carry out a series of cooperative promotional activities to promote their products. For such cross-market cooperation, it is of importance to consider the unit cost of production and the promotion cost to achieve competitive advantage and sustainability of the supply chain. We develop game-theoretic models to investigate the factors that make firms pursue cooperative promotion and how cooperative promotion affects their optimal decisions. We find that whether or not the firms join cooperative promotion mainly depends on the impacts of price, individual promotional activities, and cooperative promotional activities on demand, as well as the unit cost of production. Whether or not firms are willing to make more contribution to cooperative promotion depends on the difference between the efforts of individual promotional activities and cooperative promotional activities. In addition, as the consumer demand for the product increases, the firms will also increase their investments in cooperative and independent promotional activities. Moreover, as the unit cost of production and the impact of cooperative promotional activities on demand change, pursuing cooperative promotion is not necessarily more profitable than pursuing independent promotion.

3D printing technology has emerged as a high value-added industry with high efficiency that has dramatically broken away from the existing material and manufacturing industry’s human-based production system. These technologies, ranging from small parts to large structures, are rapidly developing due to the challenge of various filament materials, whereas there are significant concerns about waste filler materials, and complimentary research is needed to improve them. Polylactic acid (PLA), the representative polymer of 3D printing, contributes to minimizing environmental risks. However, although thermoplastic PLA has excellent reversible properties for heat in terms of sustainable resources, it is degraded as a low value-added material afterward. Therefore, in this study, the effect of repetitive recycling on the mechanical and thermal properties of PLA filaments was analyzed to verify and re-evaluate PLA as a renewable resource. As a result, recycled PLA has decreased tensile and flexural strength by up to 69% and 53%, respectively, compared to initial neat PLA with the increase of the number of repetitive recycling, and this demonstrates the change in the thermal properties of recycled PLA.

In this paper, the electrohydrodynamic (EHD) printing method for the flexible electronics with nanosilver ink was studied. The effect of DC voltage and air pressure on the printed nanosilver line was experimentally researched on the printing system. The necessary working voltage was above 600 V DC voltage, and when the voltage reached 1100 V, the line width increased from $100\mu \mathrm{\text{m}}$ to $600\mu \mathrm{\text{m}}$. The air supply of $10\mu \mathrm{\text{L/min}}$ resulted an obviously larger width than that of $1\mu \mathrm{\text{L/min}}$, but the printing process was unstable on the $10\mu \mathrm{\text{L/min}}$ condition. The EHD printing was applied to realize nanosilver ink line ranged from $60\mu \mathrm{\text{m}}$ to $600\mu \mathrm{\text{m}}$ and a kind of antenna pattern for radio frequency identification devices (RFID) was fabricated. This kind of EHD printing method has the advantages of high flexibility and printing resolution and shows potential prospects in the field of flexible electronics.

Ink-jet technology is a novel method for rapid deposition of accurately measured material with high precision. Consequently it has been used for applications such as, deposition of light emitting polymers and more recently for fabricating 3D objects and micro-mechanical structures. Ink-jet technology is also being applied to produce tactile maps for the visually impaired. The efficiency of the tactile maps, as outlined by psychophysical and cartographic studies of haptics, depends on its 3D features. To comprehend and control these features, detailed understanding of interaction amongst micro-drops, which are typically 50μm in diameter, is imperative. Multiphase interaction takes place between each liquid drop at impact with liquid or solid cured drops (deposited previously) and the solid substrate in an envelop of air. The behavior of micro-drops with regards to surface tension, drop coalescence among liquid and solid drops, drop impact kinetics, wettability, surface energy and drop spread has been analyzed using a computational model.

This study investigates the possibility analysis of UAV propeller made by commercial 3D printing machine. The primary experimental facility is 3D printer based on Fused Deposition Modeling method (FDM). The main methodology of this work is to construct standard test piece according to ASTM standard and use for standard test. The Polylactic Acid (PLA) and carbon fiber composite material are the main two printing materials in this work. Experimental results reveal that the strength and bending of these two materials are enough to be the propeller of middle size UAV, especially the carbon fiber composite material. This study not only confirms the application possibility of UAV propeller made by 3D printing, but also carries out the real flight test to identify performance enhancement and future application.

This study mainly aimed to make 3D printing technologies serve as the guidelines for the development of technology-oriented industries. The most important one was tasked to establish modeling technology applicable to 3D printing in view of technological development. For the substrate material of 3D printers, aside from commonly usable plastic, new carbon fiber composite substrates have been proposed. Substrates were selected for manufacturing dependent on different object characteristics. The components were manufactured mainly by focusing on small-sized aircraft components. Additionally, potential problems encountered during 3D printing were explored with feasible suggested solutions. In the aerospace industry, because of the extreme requirements for the weight reduction of aircraft components, in the past, this was limited by manufacturing difficulties. If specific shapes were required, it was highly difficult to produce a component in a single-cast production or cut from a single metal piece. Component manufacturing often had to be divided into several planning blocks, and then welding, assembly, or rivet connection was conducted. This situation was not only flawed with structural weaknesses but also extra weight. If metal powder was operable with 3D printing for integral molding, the above disadvantages could be avoided.

As a new rapid additive manufacturing technology that has emerged in recent years, 3D printing technology can realize the precise manufacturing of complex and flexible sensor structures. In this study, a sensor was fabricated by injecting silver nanowires (AgNWs) ethanol solution into stretchable polydimethylsiloxane (PDMS). The substrate was used in two design configurations through a 3D printing template method, i.e. “straight” and “wave”. Compared to the straight sensor, the structural design of the wave sensor could increase the stretch range and sensitivity. In particular, the stretch range increased by 26.1% and the sensitivity improved by 96.0%. The stretchable sensor was successfully applied in pronunciation recognition and gait detection. Therefore, the stretchable sensor is also expected to be further used in fields such as foldable phones and wearable physiological signal sensors.

Wire-directed energy deposition (wire-DED) is used to create a shape in a layer-by-layer manner by depositing a consumable welding wire, where a welding arc is the source of heat. This technology can be used to fabricate large components with higher deposition rates compared to other 3D metal printing methods. Despite these benefits, the components of wire-DED are affected by heat distortion and residual stress. Therefore, the prediction of deformation before fabrication using wire-DED is essential for determining the range of machining for the final products. In this study, the deformation and time required were evaluated using various simulation models of wire-DED.

This paper proposes a new oil painting reproduction method using 3D printing to compensate for the deficiencies of the existing methods. First, 3D reconstruction of oil paintings is completed by photogrammetry; the oil painting color and the 3D geometric information are recovered better by acquiring several sets of orthophotomaps, and modeling accuracy is ensured with a control mesh or by flattening. Next, the contours and hypsometric tints of the 3D model for oil paintings are generated using contour tracing algorithm, and the image segmentation of renderings is completed using RGB image segmentation algorithm, with the layered section extracted from each layer and the 3D geometric information converted into 2D plane information. Finally, the 3D models of oil paintings are presented through UV inkjet printing with images superimposed layer upon layer, and stereoscopic reproduction of oil paintings is completed based on the orthophotomaps printed from the 3D models.

The famous Lorenz system is studied and analyzed for a particular set of parameters originally proposed by Lorenz. With those parameters, the system has a single globally attracting strange attractor, meaning that almost all initial conditions in its 3D state space approach the attractor as time advances. However, with a slight change in one of the parameters, the chaotic attractor coexists with a symmetric pair of stable equilibrium points, and the resulting tri-stable system has three intertwined basins of attraction. The advent of 3D printers now makes it possible to visualize the topology of such basins of attraction as the results presented here illustrate.

We propose an Euler transformation that transforms a given $d$-dimensional cell complex $K$ for $d=2,3$ into a new $d$-complex $\widehat{K}$ in which every vertex is part of the same even number of edges. Hence every vertex in the graph $Ĝ$ that is the $1$-skeleton of $\widehat{K}$ has an even degree, which makes $Ĝ$ Eulerian, i.e., it is guaranteed to contain an Eulerian tour. Meshes whose edges admit Eulerian tours are crucial in coverage problems arising in several applications including 3D printing and robotics.

For $2$-complexes in ${ℝ}^2$ ($d=2$) under mild assumptions (that no two adjacent edges of a $2$-cell in $K$ are boundary edges), we show that the Euler transformed $2$-complex $\widehat{K}$ has a geometric realization in ${ℝ}^2$, and that each vertex in its $1$-skeleton has degree $4$. We bound the numbers of vertices, edges, and $2$-cells in $\widehat{K}$ as small scalar multiples of the corresponding numbers in $K$.

We prove corresponding results for $3$-complexes in ${ℝ}^3$ under an additional assumption that the degree of a vertex in each $3$-cell containing it is $3$. In this setting, every vertex in $Ĝ$ is shown to have a degree of $6$.

We also present bounds on parameters measuring geometric quality (aspect ratios, minimum edge length, and maximum angle of cells) of $\widehat{K}$ in terms of the corresponding parameters of $K$ for $d=2,3$. Finally, we illustrate a direct application of the proposed Euler transformation in additive manufacturing.

We explore efficient optimization of toolpaths based on multiple criteria for large instances of 3D printing problems. We first show that the minimum turn cost 3D printing problem is NP-hard, even when the region is a simple polygon. We develop SFCDecomp, a space filling curve based decomposition framework to solve large instances of 3D printing problems efficiently by solving these optimization subproblems independently. For the Buddha model, our framework builds toolpaths over a total of 799,716 nodes across 169 layers, and for the Bunny model it builds toolpaths over 812,733 nodes across 360 layers. Building on SFCDecomp, we develop a multicriteria optimization approach for toolpath planning. We demonstrate the utility of our framework by maximizing or minimizing tool path edge overlap between adjacent layers, while jointly minimizing turn costs. Strength testing of a tensile test specimen printed with tool paths that maximize or minimize adjacent layer edge overlaps reveal significant differences in tensile strength between the two classes of prints.

One of the most widely used 3D printing techniques is fused deposition modeling (FDM) which builds things layer by layer by dispensing molten materials through a heated nozzle. To showcase the flexibility of 3D printing, test samples were made using polylactic acid (PLA). Trial runs with Taguchi’s (L27) orthogonal array were performed. Layer thickness, printing speed, and carbon deposition (C-deposition) were the three input parameters that were improved. This was accomplished by combining principal component analysis (PCA) with multi-objective optimization based on ratio analysis (MOORA) in an integrated approach to multi-criteria optimization. The main goal of this study is to maximize the input parameters for the Industry 4.0 technological production process of embossing components. The MOORA-PCA technique finds the best combinations of process variables; for example, printing at a speed of 75mm/s, layer thickness of 0.1mm, and carbon content of 15mg yield the required results. The results of this study will help production managers and researchers choose the best FDM 3D printing methods for improving mechanical qualities and surface roughness. The economic feasibility of the 3D printing businesses may be strengthened by these research findings, which will benefit customers looking for ecologically friendly items.

Peri-implant debris certainly lead to osteolysis, necrosis, pseudotumor formation, tissue granulation, fibrous capsule contractions, and even implant failure. For the three-dimensional (3D) printed cage, impaction during cage insertion is one of the most potential sources of fracture debris. A finite-element study was carried out to reduce the impact-induced debris of the 3D-printed cage. This study focused on the design strategy of solid and cellular structures along the load-transferring path. Using the finite-element method, the cellular structure of the transforaminal lumbar interbody fusion (TLIF) cage was systematically modified in the following four variations: a noncellular cage (NC), a fully cellular (FC) cage, a solid cage with a cellular structure in the middle concave (MC) zone, and a strengthened cage (SC) in the MC zone. Three comparison indices were considered: the stresses at the cage-instrument interfaces, in the MC zone, and along the specific load-transferring path. The NC and FC were the least and most highly stressed variations at the cage-instrument interfaces and in the MC zone, respectively. Along the entirely load-transferring path, the FC was still the most highly stressed variation. It showed a higher risk of stress fracture for the FC cage. For the MC and SC, the MC zone was consistently more stressed than the directly impacted zone. The further strengthened design of the SC had a lower peak stress (approximately 29.2%) in the MC zone compared with the MC. Prior to 3D printing, the load-transferring path from the cage-instrument interfaces to the cage-tissue interfaces should be determined. The cage-instrument interfaces should be printed as a solid structure to avoid impact-induced fracture. The other stress-concentrated zones should be cautiously designed to optimize the coexistence strategy of the solid and cellular structures.