Experimental Modal Analysis and Characterization of Additively Manufactured Polymers

Experimental Evaluation of a Granular Damping Element

Due to their advantages-longer internal force delay compared to bulk materials, resistance to harsh conditions, damping of a wide frequency spectrum, insensitivity to ambient temperature, high reliability and low cost-granular materials are seen as an opportunity for the development of high-performance, lightweight vibration-damping elements (particle dampers). The performance of particle dampers is affected by numerous parameters, such as the base material, the size of the granules, the flowability, the initial prestress, etc. In this work, a series of experiments were performed on specimens with different combinations of influencing parameters. Energy-based design parameters were used to describe the overall vibration-damping performance. The results provided information for a deeper understanding of the dissipation mechanisms and their mutual correlation, as well as the influence of different parameters (base material, granule size and flowability) on the overall damping performance. A comparison of the performance of particle dampers with carbon steel and polyoxymethylene granules and conventional rubber dampers is given. The results show that the damping performance of particle dampers can be up to 4 times higher compared to conventional bulk material-based rubber dampers, even though rubber as a material has better vibration-damping properties than the two granular materials in particle dampers. However, when additional design features such as mass and stiffness are introduced, the results show that the overall performance of particle dampers with polyoxymethylene granules can be up to 3 times higher compared to particle dampers with carbon steel granules and conventional bulk material-based rubber dampers.

Influence of 3D Printing Direction in PLA Acoustic Guitars on Vibration Response

The design of musical instruments is a discipline that is still carried out in an artisanal way, with limitations and high costs. With the additive manufacturing technique, it is possible to obtain results for the generation of not only electrical but also acoustic instruments. However, it is necessary to generate a procedure to evaluate the influence of the process on the final result of the acoustics obtained. This study focuses on investigating the relationship between the construction of acoustic guitars and their final sound. The reinforcement structures at the top of the instrument are analysed, as well as how this design affects the vibratory behaviour of the top in the first five vibratory modes. Specifically, this article presents a procedure for the design of customised acoustic guitars using additive manufacturing through parametrisation and a vibrational analysis of the designed tops using finite element (FEA) and experimental physical tests, in order to develop a methodology for the study of stringed instruments. As a result, an 11% increase in the high-frequency response was achieved with a printing direction of +45°, and a reduction in the high-frequency response with ±45°. In addition, at high frequencies, a relative error of 5% was achieved with respect to the simulation. This work fulfils an identified need to study the manufacture of acoustic guitars using polylactic acid (PLA), and to be able to offer the musician a customised instrument. This represents a breakthrough in the use of this manufacturing technology, extending its relationship with product design.

Advancements in Functionally Graded Polyether Ether Ketone Components: Design, Manufacturing, and Characterisation Using a Modified 3D Printer

Functionally Graded Materials represent the next generation of engineering design for metal and plastic components. In this research, a specifically modified and optimised 3D printer was used to manufacture functionally graded polyether ether ketone components. This paper details the design and manufacturing methodologies used in the development of a polyether ether ketone printer capable of producing functionally graded materials through the manipulation of microstructure. The interaction of individually deposited beads of material during the printing process was investigated using scanning electron microscopy, to observe and quantify the porosity levels and interlayer bonding strength, which affects the quality of the final parts. Specimens were produced under varying process conditions and tested to characterise the influence of the process conditions on the resulting material properties. The specimens printed at high enclosure temperatures exhibited greater strength than parts printed without the active addition of heat, due to improved bond formation between individual layers of the print and a large degree of crystallinity through maintenance at these elevated temperatures.

Special Issue Editorial: Applications of 3D Printing for Polymers

Polymer 3D printing is an emerging technology highly relevant in diverse industries, including medicine, electronics, and robotics [...]

Sustainable Polymer Composites Manufacturing through 3D Printing Technologies by Using Recycled Polymer and Filler

In the last years, the excessive use of plastic and other synthetic materials, that are generally difficult to dispose of, has caused growing ecological worries. These are contributing to redirecting the world’s attention to sustainable materials and a circular economy (CE) approach using recycling routes. In this work, bio-filaments for the Fused Filament Fabrication (FFF) 3D printing technique were produced from recycled polylactic acid (PLA) and artisanal ceramic waste by an extrusion process and fully characterized from a physical, thermal, and mechanical point of view. The data showed different morphological, thermal, rheological, and mechanical properties of the two produced filaments. Furthermore, the 3D objects produced from the 100% recycled PLA filament showed lower mechanical performance. However, the results have demonstrated that all the produced filaments can be used in a low-cost FFF commercial printer that has been modified with simple hand-made operations in order to produce 3D-printed models. The main objective of this work is to propose an example of easy and low-cost application of 3D printing that involves operations such as the reprocessing and the recyclability of materials, that are also not perfectly mechanically performing but can still provide environmental and economic benefits.

Failures and Flaws in Fused Deposition Modeling (FDM) Additively Manufactured Polymers and Composites

In this review, the potential failures and flaws associated with fused deposition modeling (FDM) or fused filament fabrication (FFF) 3D printing technology are highlighted. The focus of this article is on presenting the failures and flaws that are caused by the operational standpoints and which are based on the many years of experience with current and emerging materials and equipment for the 3D printing of polymers and composites using the FDM/FFF method. FDM or FFF 3D printing, which is also known as an additive manufacturing (AM) technique, is a material processing and fabrication method where the raw material, usually in the form of filaments, is added layer-by-layer to create a three-dimensional part from a computer designed model. As expected, there are many advantages in terms of material usage, fabrication time, the complexity of the part, and the ease of use in FDM/FFF, which are extensively discussed in many articles. However, to upgrade the application of this technology from public general usage and prototyping to large-scale production use, as well as to be certain about the integrity of the parts even in a prototype, the quality and structural properties of the products become a big concern. This study provides discussions and insights into the potential factors that can cause the failure of 3D printers when producing a part and presents the type and characteristics of potential flaws that can happen in the produced parts. Common defects posed by FDM printing have been discussed, and common nondestructive detection methods to identify these flaws both in-process and after the process is completed are discussed. The discussions on the failures and flaws in machines provides useful information on troubleshooting the process if they happen, and the review on the failures and flaws in parts helps researchers and operators learn about the causes and effects of the flaws in a practical way.

Experimental Investigation and Prediction of Mechanical Properties in a Fused Deposition Modeling Process

Additive manufacturing, also known as three-dimensional printing, is a computer-controlled advanced manufacturing process that produces three-dimensional items by depositing materials directly from a computer-aided design model, usually in layers. Due to its capacity to manufacture complicated objects utilizing a wide range of materials with outstanding mechanical qualities, fused deposition modeling is one of the most commonly used additive manufacturing technologies. For printing high-quality components with appropriate mechanical qualities, such as tensile strength and flexural strength, the selection of adequate processing parameters is critical. Experimentally, the influence of process parameters such as the raster angle, printing orientation, air gap, raster width, and layer height on the tensile strength of fused deposition modeling printed items was examined in this work. Through analysis of variance, the impact of each parameter was measured and rated. The system’s response was predicted using an adaptive neuro-fuzzy technique and an artificial neural network. In Minitab software, the Box-Behnken response surface experimental design was used to generate 46 experimental trials, which were then printed using acrylonitrile butadiene styrene polymer materials on a three-dimensional forge dreamer II fused deposition modelling printing machine. The results revealed that the raster angle, air gap, and raster width had significant impacts on the tensile strength. The adaptive neuro-fuzzy approach and artificial neural network predicted tensile strength accurately with an average percentage error of 0.0163 percent and 1.6437 percent, respectively. According to the findings, the model and experimental data are in good agreement.