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This paper aims to present the methodology and results of the experimental characterization of three-dimensional (3D) printed acrylonitrile butadiene styrene (ABS) and polycarbonate (PC) parts utilizing digital image correlation (DIC).

Tensile and shear characterizations of ABS and PC 3D-printed parts were performed to determine the extent of anisotropy present in 3D-printed materials. Specimens were printed with varying raster ([+45/−45], [+30/−60], [+15/−75] and [0/90]) and build orientations (flat, on-edge and up-right) to determine the directional properties of the materials. Tensile and Iosipescu shear specimens were printed and loaded in a universal testing machine utilizing two-dimensional (2D) DIC to measure strain. The Poisson’s ratio, Young’s modulus, offset yield strength, tensile strength at yield, elongation at break, tensile stress at break and strain energy density were gathered for each tensile orientation combination. Shear modulus, offset yield strength and shear strength at yield values were collected for each shear combination.

Results indicated that raster and build orientations had negligible effects on the Young’s modulus or Poisson’s ratio in ABS tensile specimens. Shear modulus and shear offset yield strength varied by up to 33 per cent in ABS specimens, signifying that tensile properties are not indicative of shear properties. Raster orientation in the flat build samples reveals anisotropic behavior in PC specimens as the moduli and strengths varied by up to 20 per cent. Similar variations were observed in shear for PC. Changing the build orientation of PC specimens appeared to reveal a similar magnitude of variation in material properties.

This article tests tensile and shear specimens utilizing DIC, which has not been employed previously with 3D-printed specimens. The extensive shear testing conducted in this paper has not been previously attempted, and the results indicate the need for shear testing to understand the 3D-printed material behavior fully.

Tensile property is one basic mechanics performance of the fabric. In general, not only the tensile values of the fabric are needed, but also the dynamic changing process under the tension is also needed. However, the dynamic tensile process cannot be included in the common testing methods by using the instruments after fabric weaving.

By choosing the weft yarn and warp yarn in the fabric as the minimum modeling unit, 1:1 finite element model of the whole woven fabrics was built by using AutoCAD software according to the measured geometric parameters of the fabrics and mechanical parameters of yarns. Then, the fabric dynamic tensile process was simulated by using the ANSYS software. The stress–strain curve along the warp direction and shrinkage rate curve along the weft direction of the fabrics were simulated. Meanwhile, simulation results were verified by comparing to the testing results.

It is shown that there are four stages during the fabric tensile fracture process along the warp direction under the tension. The first stage is fabric elastic deformation. The second stage is fabric yield deformation, and the change rate of stress begins to slow down. The third stage is fiber breaking, and the change of stress fluctuates since the breaking time of the fibers is different. The fourth stage is fabric breaking.

In this paper, the dynamic tensile process of blended woven fabrics was studied by using finite element method. Although there are differences between the simulation results and experimental testing results, the overall tendency of simulation results is the same as the experimental testing results.

This paper aims to present the influences of several production variables on the mechanical properties of specimens manufactured using fused deposition modeling (FDM) with polylactic acid (PLA) as a media and relate the practical and experimental implications of these as related to stiffness, strength, ductility and generalized loading.

A two-factor-level Taguchi test matrix was defined to allow streamlined mechanical testing of several different fabrication settings using a reduced array of experiments. Specimens were manufactured and tested according to ASTM E8/D638 and E399/D5045 standards for tensile and fracture testing. After initial analysis of mechanical properties derived from mechanical tests, analysis of variance was used to infer optimized production variables for general use and for application/load-specific instances.

Production variables are determined to yield optimized mechanical properties under tensile and fracture-type loading as related to orientation of loading and fabrication.

The relation of production variables and their interactions and the manner in which they influence mechanical properties provide insight to the feasibility of using FDM for rapid manufacturing of components for experimental, commercial or consumer-level use.

This paper is the first report of research on the characterization of the mechanical properties of PLA coupons manufactured using FDM by the Taguchi method. The investigation is relevant both in commercial and consumer-level aspects, given both the currently increasing utilization of 3D printers for component production and the viability of PLA as a renewable, biocompatible material for use in structural applications.

The overall aim of this research work was the improvement of the failure behavior of printed circuit boards (PCBs). In order to describe the mechanical behavior of PCBs under cyclic thermal loads, thin copper layers were characterized. The mechanical properties of these copper layers were determined in cyclic four-point bend tests and in cyclic tensile-compression tests, as their behavior under changing tensile and compression loads needed to be evaluated.

Specimens for the four-point bend tests were manufactured by bonding 18-μm-thick copper layers on both sides of 10-mm-thick silicone plates. The silicone was characterized in tensile, shear and blow-up tests to provide input data for a hyperelastic material model. Specimens for the cyclic tensile-compression tests were produced in a compression molding process. Four layers of glass fiber-reinforced epoxy resin (thickness 90 μm) and five layers of copper (thickness 60 μm) were applied.

The results showed that, due to the hyperelastic material behavior of silicone, the four-point bend tests were applicable only for small strains, while the cyclic tensile-compression tests could successfully be applied to characterize thin copper foils in tensile and compression up to 1 percent strain.

Thin copper layers (foils) could be characterized successfully under cyclic tensile and compression loads.

The purpose of this paper is to characterize mechanical properties (tensile, compressive and flexural) for the three-dimensional printing (3DP) process, using various common recommended infiltrate materials and post-processing conditions.

A literature review is conducted to assess the information available related to the mechanical properties, as well as the experimental methodologies which have been used when investigating the 3D printing process characteristics. Test samples are designed, and a methodology to measure infiltrate depths is presented. A full factorial experiment is conducted to collect the tensile, compressive and bending forces for a set of infiltrates and build orientations. The impact of the infiltrate type and depth with respect to the observed strength characteristics is evaluated.

For most brittle materials, the ultimate compression strength is much larger than the ultimate tensile strength, which is shown in this work. Unique stress–strain curves are generated from the infiltrate and build orientation conditions; however, the compressive strength trends are more consistent in behavior compared to the tensile and flexural results. This comprehensive study shows that infiltrates can significantly improve the mechanical characteristics, but performance degradation can also occur, which occurred with the Epsom salts infiltrates.

More experimental research needs to be performed to develop predictive models for design and fabrication optimization. The material-infiltrate performance characteristics vary per build orientation; hence, experimental testing should be performed on intermediate angles, and a double angle experiment set should also be conducted. By conducting multiple test scenarios, it is now understood that this base material-infiltrate combination does not react similar to other materials, and any performance characteristics cannot be easily predicted from just one study.

These results provide a foundation for a process design and post-processing configuration database, and downstream design and optimization models. This research illustrates that there is no “best” solution when considering material costs, processing options, safety issues and strength considerations. This research also shows that specific testing is required for new machine–material–infiltrate combinations to calibrate a performance model.

There is limited published data with respect to the strength characteristics that can be achieved using the 3DP process. No published data with respect to stress–strain curves are available. This research presents tensile, compressive and flexural strength and strain behaviors for a wide variety of infiltrates, and post-processing conditions. A simple, unique process is presented to measure infiltrate depths. The observed behaviors are non-linear and unpredictable.

The purpose of this study is to understand the behavior of hybrid bio-composites under varied applications.

Fabrication methods and material characterization of various hybrid bio-composites are analyzed by studying the tensile, impact, flexural and hardness of the same. The natural fiber is a manufactured group of assembly of big or short bundles of fiber to produce one or more layers of flat sheets. The natural fiber-reinforced composite materials offer a wide range of properties that are suitable for many engineering-related fields like aerospace, automotive areas. The main characteristics of natural fiber composites are durability, low cost, low weight, high specific strength and equally good mechanical properties.

The tensile properties like tensile strength and tensile modulus of flax/hemp/sisal/Coir/Palmyra fiber-reinforced composites are majorly dependent on the chemical treatment and catalyst usage with fiber. The flexural properties of flax/hemp/sisal/coir/Palmyra are greatly dependent on fiber orientation and fiber length. Impact properties of flax/hemp/sisal/coir/Palmyra are depended on the fiber content, composition and orientation of various fibers.

This study is a review of various research work done on the natural fiber bio-composites exhibiting the factors to be considered for specific load conditions.

This paper aims to review recent reports on mechanical properties of Sn-Bi and Sn-Bi-X solders (where X is an additional alloying element), in terms of the tensile properties, hardness and shear strength. Then, the effects of alloying in Sn-Bi solder are compared in terms of the discussed mechanical properties. The fracture morphologies of tensile shear tested solders are also reviewed to correlate the microstructural changes with mechanical properties of Sn-Bi-X solder alloys.

A brief introduction on Sn-Bi solder and reasons to enhance the mechanical properties of Sn-Bi solder. The latest reports on Sn-Bi and Sn-Bi-X solders are combined in the form of tables and figures for each section. The presented data are discussed by comparing the testing method, technical setup, specimen dimension and alloying element weight percentage, which affect the mechanical properties of Sn-Bi solder.

The addition of alloying elements could enhance the tensile properties, hardness and/or shear strength of Sn-Bi solder for low-temperature solder application. Different weight percentage alloying elements affect differently on Sn-Bi solder mechanical properties.

This paper provides a compilation of latest report on tensile properties, hardness, shear strength and deformation of Sn-Bi and Sn-Bi-X solders and the latest trends and in-depth understanding of the effect of alloying elements in Sn-Bi solder mechanical properties.

Fused deposition modeling (FDM) is being increasingly used in automotive and aerospace industries because of its ability to produce specimens having difficult geometrical shape. However, owing to lack of critical information regarding the reliability and mechanical properties of FDM-printed parts at various designs, the use of 3D printed parts in these industries is limited. Therefore, the purpose of this paper is to investigate the impact of process parameters of FDM on the tensile strength of open-hole specimen printed using in-house-fabricated polylactic acid (PLA).

In the present study, three process parameters, namely, raster angle, layer thickness and raster width, are selected for investigation of tensile strength. To produce the tensile specimens in the FDM machine, the PLA filament is used which is fabricated from PLA granules using a single-screw extruder. Further, the experimental values are measured and critically analysed. Failure modes under tests are studied using scanning electron microscopy (SEM).

Results indicate that the raster angle has a significant effect on the tensile strength of open-hole tensile specimen. Specimens built with 0° raster angle, 200-µm layer thickness and 500-µm raster width obtained maximum tensile strength.

In this work, a new concept of testing a plate that has a rectangular shape and a circular hole at the centre is tested. Open-hole tensile test standard ASTM D5766 has been implemented for the first time for the FDM process.

The paper aims to propose an approach to intelligent evaluation of the tensile test. A robotized system is used that performs the fabrics tensile test and estimates the extensibility of the samples using a feed‐forward neural network while trying to imitate the human expert estimation.

The specifications of the tensile test are derived by an extensive observation of the respective experts' estimation performance. The fabric sample size and the experimental conditions are specified. Linguistic values of the term “fabric extensibility” are extracted through a knowledge acquisition process. The tensile test is performed by a robot manipulator with a simple gripper and the experimental measurements (force, strain) are fed online into a neural network. The network is trained according to the extensibility estimations of the experts. The trained network is tested in estimating unknown fabric's extensibility.

The results demonstrate that the system is capable of estimating the extensibility of new fabrics.

This work can be integrated in the robotized sewing process with intelligent control where the fabric's extensibility in terms of linguistic values is necessary. The proposed system initiates a new approach, in which the fabric properties are expressed and used in a way that will facilitate the introduction of the artificial intelligence methods into the clothing industry.

Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.

The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R²) and mean absolute error (MAE).

Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.

The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.

This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.