Mechanical testing of 3D printed samples made of flexible TPU material

<div class="section abstract"><div class="htmlview paragraph">Additive Manufacturing (AM) techniques, particularly Fusion Deposition Modeling (FDM), have received considerable interest due to their capacity to create complex structures using a diverse array of materials. The objective of this study is to improve the process control and efficiency of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material by creating a predictive model using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The study investigates the impact of FDM process parameters, including layer height, nozzle temperature, and printing speed, on key printing attributes such as tensile strength, flexibility, and surface quality. Several experimental trials are performed to gather data on these parameters and their corresponding printing attributes. The ANFIS predictive model is built using the collected dataset to forecast printing characteristics by analyzing input process parameters. The ANFIS model utilizes the learning capabilities of neural networks and fuzzy logic systems to analyze the intricate relationships within the FDM process. This model allows for precise predictions of printing outcomes. The model shows its ability to precisely forecast printing attributes, enabling the determination of ideal process parameter configurations for enhanced FDM performance with TPU material. The proposed Adaptive Neuro-Fuzzy Inference System (ANFIS) predictive model presents a methodical strategy for optimizing Fused Deposition Modeling (FDM) parameters. This model serves as a valuable tool for manufacturers to improve productivity and product quality in additive manufacturing operations using Thermoplastic Polyurethane (TPU) material. This research enhances the comprehension of FDM processes and provides practical recommendations for optimizing AM operations in diverse industrial applications.</div></div>

This study aims to explore and select a sample of three-dimensional (3D) printed lattice structures suitable for fabrication of a lumbar brace. In particular, the study compared honeycomb, gyroid, and X-shape lattice structures. Thirty-six samples with two thicknesses, two pattern repeats, three lattice structures, and three 3D printing manufacturing methods and material variables were fabricated to evaluate tensile strength, flexural strength, weight, and density. Mechanical evaluation revealed that the tensile and flexural strengths of the honeycomb structure were higher than those of other structures. In addition, the fused deposition modeling (FDM) method using thermoplastic polyurethane (TPU) material had higher tensile and flexural strengths compared with the other two printing methods and materials. The honeycomb structure weighed the most, followed by the X-shape and gyroid structures. The sample made of PolyJet method with Agilus material showed higher values of weight and density than the other samples. Based on the experimental results, it is considered that TPU material, FDM, and selective laser sintering printing methods are suitable for production of the lumbar support brace because it is flexible and allows body movement but has moderate strength and density. By adjusting the pattern repeat and thickness of the lattice structure variable, we can determine the structure that is most suitable for lumbar support. Considering the lightweight requirements of lumbar support, future studies should devise ways to improve the lightweight properties of samples.

The thermoplastic polyurethane (TPU) material is an elastomer that can be used for inflatable products. Fused deposition modelling (FDM) is a widely used additive manufacturing process for TPU material due to the capability of generating complex structures with low cost. However, TPU is soft and thus difficult to be extruded as continuously and uniformly as hard materials such as polylactide by FDM. Inappropriate extruder structure and speed settings can lead to filament buckling problem, resulting in poor material filling quality, long printing time and low printing success rate. This paper aims at improving the FDM printing efficiency of TPU inflatable products by adding lateral support to the filament and finding out the appropriate speed ranges for different wall features and thicknesses. Firstly, a filament guide sheet is designed as being inserted into the gap between the drive gears and the bottom frame of the gear chamber in order to prevent the soft TPU filament from buckling. Secondly, inflatable product wall features are classified into floors, roofs and sidewalls and experiment for finding the relationship between printing speed and airtightness is carried out. In order to verify the proposed solution, wall features are printed and the material fillings obtained under different printing speeds are compared by measuring the airtightness of the wall features. Results show that the proposed filament guide sheet mitigates filament buckling, and the speed range that meets the airtightness requirement can be found for various wall features and thicknesses. In summary, the sealing of the filament feeding channel between the drive gears and the nozzle, as well as the speed optimisation according to product features, are essential for the efficient printing of TPU inflatable products.

<div class="section abstract"><div class="htmlview paragraph">Fused Deposition Modeling (FDM) is a highly adaptable additive manufacturing method that is extensively employed for creating intricate structures using a range of materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability, making it well-suited for use in industries such as footwear, automotive, and consumer goods. Hoses, gaskets, seals, external trim, and interior components are just a few of the many uses for thermoplastic polyurethanes (TPU) in the automobile industry. The objective of this study is to enhance the performance of Fused Deposition Modeling (FDM) by optimizing the parameters specifically for Thermoplastic Polyurethane (TPU) material. This will be achieved by employing a Taguchi-based Grey Relational Analysis (GRA) method. The researchers conducted experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses like dimensional accuracy, surface finish, and mechanical properties. The Taguchi method enabled the systematic exploration of parameters through the design of experiments (DOE). The experimental data was analyzed using Grey Relational Analysis (GRA) to determine the optimal parameter settings. The GRA methodology offers a comprehensive approach to assess and prioritize various performance criteria, taking into account the inherent uncertainties in the manufacturing process. The results demonstrated the efficacy of the Taguchi-based GRA method in pinpointing the optimal parameter combinations for improving the printing quality and efficiency of TPU components. This study enhances the comprehension of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material and provides a useful framework for optimizing the manufacturing process. Manufacturers can enhance printing productivity, quality, and reliability by utilizing Taguchi-based GRA. This, in turn, promotes the wider use of FDM technology in various industrial applications that demand flexible and long-lasting components.</div></div>

<div class="section abstract"><div class="htmlview paragraph">Additive Manufacturing (AM), specifically Fusion Deposition Modeling (FDM), has transformed the manufacturing industry by allowing the creation of complex structures using a wide range of materials. The objective of this study is to enhance the FDM process for Thermoplastic Polyurethane (TPU) material by utilizing the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) optimization method. The study examines the influence of FDM parameters, such as layer height, nozzle temperature, and infill density, on important characteristics of the printing process, such as tensile strength, flexibility, and surface finish. The collection of experimental data is achieved by conducting systematic FDM printing trials that cover a variety of parameter combinations. The TOPSIS optimization method is utilized to determine the optimal parameter settings by evaluating each parameter combination against the ideal and anti-ideal solutions. This method determines the optimal parameter configuration that maximizes the overall printing quality by considering multiple objectives simultaneously. The effectiveness of the TOPSIS-optimized FDM process is assessed using statistical analysis and compared to the baseline outcomes. The proposed TOPSIS optimization method offers a valuable tool for optimizing the AM process. It allows manufacturers to enhance productivity and product quality while minimizing production costs. This study enhances the comprehension of Fused Deposition Modeling (FDM) techniques using Thermoplastic Polyurethane (TPU) material and provides valuable knowledge for improving Additive Manufacturing (AM) operations in different industrial sectors.</div></div>

Effects of printing parameters of fused deposition modeling on mechanical properties, surface quality, and microstructure of PEEK

This research is motivated by the increasing utilization of 3D print technology across various sectors. Understanding the appropriate materials is crucial for the effective application of this technology. The aim of this study is to analyse the utilization of Thermoplastic Polyurethane (TPU) material through 3D print as a replacement for bicycle brake pads. The research method involves comparing the strength and durability of TPU material through tensile and wear tests, based on different brake pad patterns, infill geometries, and infill densities in 3D print. The patterns used are derived from two conventional brake pad designs, namely the straight-pattern and the V-pattern. The infill geometries utilized are concentric, gyroid, and zigzag, with infill densities of 25%, 50%, 75%, and 100%. The tensile test results indicate that the gyroid infill geometry for the straight pattern exhibits high strength, while the concentric infill geometry for the V pattern demonstrates high strength. TPU material is found to be 3-4 times stronger than conventional brake pads. However, the wear test results show minimal difference between TPU material and conventional brake pads, but the resistance caused by TPU material is greater. Based on the post-wear test analysis of TPU brake pad shapes, the straight pattern displays better durability in retaining its shape. Both materials possess their own strengths and weaknesses, highlighting the need for further research and improvement to ensure the feasibility of this development.

Fused Deposition Modeling or FDM is a 3D printing technology that is commonly used in manufacturing processes based on Additive Manufacturing Technology. One of the materials that can be used on FDM machines is thermoplastic polyurethane (TPU). One measure of the quality of printed results is the machine's accuracy in producing workpieces that have the smallest possible dimensional error. So this research aims to obtain the printing parameters that have the most influence on print results and find out the optimal combination of printing process parameters on the machine to produce the smallest dimensional error for TPU material. The design of experiment method used is 2k factorial design using 4 process parameters, 2 levels and 3 responses. The parameters used are nozzle temperature, print speed, fill density, and enclosure box. The optimization results obtained an optimal combination of printing process parameters to produce the smallest dimensional error, namely nozzle temperature of 210°C, print speed of 30 mm/s, fill density of 100%, and not using an enclosure box.

The purpose of this study was to develop a highly comfortable 3D male hip protector using 3D modeling and printing technologies. The hip protector pads and patterns were devised using 3D human body shapes, and three types of pads were chosen in consideration of snowboarding motions. The three types of pads were as follows: first, the original type with no hole; second, an inner open type with an incision on the inside; and third, an outer open type, with an incision on the outside. Another variable of the protective pads was the material: 3D printed thermoplastic polyurethane (TPU) pad + ethylene–vinyl acetate (EVA) foam or only EVA foam. Six types of pad prototypes were 3D printed and evaluated for subjective wearing comfort. Subjective comfort, fit, activity comfort, and shock absorption were evaluated on an 11-point Likert scale. The study results showed that protectors printed using TPU material were not different from the results of 3D modeling. The evaluation results revealed that comfort, fit, and motion comfort were all negatively evaluated by subjects when wearing the original pad. While fit, comfort, and motion comfort were all positively evaluated by subjects when wearing the outer open-type pad, and comfort and motion comfort were positively evaluated by subjects when wearing the inner open-type pad. With respect to materials, pads made with the 3D printing (TPU) and EVA foam combination provided the best results in terms of overall comfort, buttocks comfort, and activity comfort.

<div class="section abstract"><div class="htmlview paragraph">Fused Deposition Modeling (FDM) is a widely recognized additive manufacturing method that is highly regarded for its ability to create complex structures using thermoplastic materials. Thermoplastic Polyurethane (TPU) is a highly versatile material known for its flexibility and durability. TPU has several applications, including automobile instrument panels, caster wheels, power tools, sports goods, medical equipment, drive belts, footwear, inflatable rafts, fire hoses, buffer weight tips, and a wide range of extruded film, sheet, and profile applications.. The primary objective of this study is to enhance the FDM parameters for TPU material and construct regression models that can accurately forecast printing performance. The study involved conducting experimental trials to examine the impact of key FDM parameters, such as layer thickness, infill density, printing speed, and nozzle temperature, on critical responses, including dimensional accuracy, surface quality, and mechanical properties. The utilization of design of experiments (DOE) methodology enabled a methodical exploration of parameters. Statistical techniques were employed to develop regression models that establish relationships between process parameters and performance indicators. These models offer a prognostic instrument for optimizing FDM parameters and attaining desired printing results. The results demonstrated the effectiveness of the regression models in accurately forecasting the printing performance for TPU material. The models provide valuable insights into the optimal parameter configurations for maximizing printing efficiency, quality, and mechanical robustness. This study enhances the comprehension of Fused Deposition Modeling (FDM) for Thermoplastic Polyurethane (TPU) material and provides useful techniques for optimizing the manufacturing process. Manufacturers can improve printing productivity and quality by utilizing regression models, thereby promoting the wider use of FDM technology in industries that need flexible and durable components.</div></div>

This study investigates the influence of key fused deposition modeling (FDM) process parameters, namely, print speed, infill percentage, layer thickness, and layer width, on the tensile properties of PLA specimens produced using 3D printing technology. A Taguchi L9 orthogonal array was employed to design the experiments efficiently, enabling the systematic evaluation of parameter effects with fewer tests. Tensile strength and elongation at break were measured for each parameter combination, and statistical analyses, including the signal-to-noise (S/N) ratio and analysis of variance (ANOVA), were conducted to identify the most significant factors. The results showed that infill percentage significantly affected tensile strength, while layer thickness was the dominant factor influencing elongation. The highest tensile strength (47.84 MPa) was achieved with the parameter combination of 600 mm/s print speed, 100% infill percentage, 0.4 mm layer thickness, and 0.4 mm layer width. A linear regression model was developed to predict tensile strength with an R2 value of 83.14%, and probability plots confirmed the normal distribution of the experimental data. This study provides practical insights into optimizing FDM process parameters to enhance the mechanical performance of PLA components, supporting their use in structural and functional applications.

3D printing technology has been widely used in various fields, such as biomedicine, clothing design, and aerospace, due to its personalized customization, rapid prototyping of complex structures, and low cost. However, the application of 3D printing technology in the field of non-pneumatic tires has not been systematically studied. In this study, we evaluated the application of potential thermoplastic polyurethanes (TPU) materials based on FDM technology in the field of non-pneumatic tires. First, the printing process of TPU material based on fused deposition modeling (FDM) technology was studied through tensile testing and SEM observation. The results show that the optimal 3D printing temperature of the selected TPU material is 210 °C. FDM technology was successfully applied to 3D printed non-pneumatic tires based on TPU material. The study showed that the three-dimensional stiffness of 3D printed non-pneumatic tires is basically 50% of that obtained by simulation. To guarantee the prediction of the performance of 3D printed non-pneumatic tires, we suggest that the performance of these materials should be moderately reduced during the structural design for performance simulation.

Fused deposition modeling (FDM) is one of the additive manufacturing (AM) methods widely used in many divisions, especially medical implants and aerospace, due to capabilities to build complex 3D objects and geometries. However, quality and dimensional accuracy of the FDM parts are significantly influenced by the various FDM process parameters including filament wire material. In the present work, new filament wire material Thermoplastic Polyurethane (TPU) was utilized to produce FDM parts. Hence, deciding the optimum process parameters is very critical to produce the FDM parts with good surface quality (Ra) and dimensional accuracy (Δd) concurrently using TPU material. In this paper, the author has contributed to determine the optimum 3D printing process parameters to improve the quality and accuracy for the new filament wire material Thermoplastic Polyurethane (TPU) using multi-attribute decision making (MADM) methods namely Gray Relational Analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS). Further, the results of GRA and TOPSIS techniques were compared and concluded that TOPSIS method substantially reduced the surface roughness to a value of 12% contrast to the GRA method whereas the dimensional deviation accuracy increased to 6.25% over the GRA method.

The research presented in this article represents a further stage in studies on the strength of components printed using 3D printing technology, specifically FDM (Fused Deposition Modelling). The article presents the results of tensile strength tests on samples printed from PA12 and PA12+CF15 materials, while previous studies by the author focused on PLA material. Basic material data provided by manufacturers and distributors of materials used in the FDM method, such as tensile strength and Young’s modulus, refer to the most favourable model orientation during printing. However, in additive technologies, particularly FDM, the constructed object shows significant layering differences (in the Z direction). The direction of material deposition (in the XY plane) is also crucial. Additionally, the strength is influenced by the degree and type of infill within the model and the temperature during printing. For these reasons, it is essential to understand the relationship between technological parameters and the resulting strength for specific materials. This study aimed to determine the tensile strength of samples printed with varying infill percentages. In the context of the new material, PA12+CF15, it is essential to understand how the addition of carbon fibers affects the mechanical properties of prints compared to traditional materials, such as PA12 and PLA. Carbon fibers can significantly increase the strength and stiffness of the composite, potentially leading to applications in producing parts with high strength requirements. Therefore, studying the strength of materials concerning various printing parameters is crucial for developing the potential of FDM technology and its industrial applications. PA12+CF15 is composed of polyamide 12 (PA12), a thermoplastic material with good chemical resistance, abrasion resistance, and flexibility. The addition of 15% carbon fibers (CF15) reinforces the composite structure, leading to increased stiffness, mechanical strength, and deformation resistance. The study shows that this addition enhances PA12’s strength by approximately 13%, also facilitating printing by reducing shrinkage.

Auxetic materials, known as materials with negative Poisson’s ratio (NPR), have many promising application areas. However, there are only few natural and man-made materials such as certain living bone tissues, certain rocks and minerals, polymeric honeycombs, microporous polytetrafluoroethylene (PTFE), foams, and carbon-fiber-reinforced epoxy composite laminate panels that possess this property. In recent years, various auxetic material structures have been designed and fabricated for diverse applications that utilized normal materials which follow Hooke’s law but still show the NPR properties. One of the applications is body protection pads that are comfortable to wear and effective in protecting body parts by reducing impact force and preventing injuries in high-risk individuals such as elderly people, industry workers, law enforcement and military personnel, and sports players. It is important to develop new body protectors that best combine each individual’s requirements for wearing comfort (flexible, light-weight), ease of fitting (customized), ensured protection, and cost-effectiveness. The protection pad would be made from multilayer materials and adaptive structures to achieve unique multifunctional properties such as high hardness, impact toughness, light weight, and excellent shock absorption suitable for the needs. This paper reports an integrated theoretical, computational (finite element analysis), and experimental investigation conducted for typical auxetic polymeric materials that exhibit negative Poisson’s ratio (NPR) effect. Parametric 3D CAD models of auxetic polymeric structures such as re-entrant hexagonal cells and arrowhead were developed. Then, key structural characteristics of protectors were evaluated through static analyses of FEA models. In addition, impact/shock analyses were conducted through dynamic analyses of FEA models to validate the results obtained from the static analyses. Particularly, an advanced additive manufacturing (3D printing) technique was used to build prototypes of the auxetic polymeric structures. Specifically, three different materials typically used for FDM (Fused Deposition Modeling) technology such as Polylactic acid (PLA) and thermoplastic polyurethane (TPU) material (NinjaFlex® and SemiFlex®) were used for different stiffness and shock-absorption performances. The 3D printed prototypes were then tested and the results were compared with the computational prediction. The results showed that the auxetic material can be effective for body protection pads. Each structure and material had unique structural properties such as stiffness, Poisson’s ratio, and efficiency in shock absorption. Particularly, auxtetic structures showed better shock absorption performance than non-auxetic ones. The mechanism for ideal input force distribution or shunting could be suggested for designing protectors using various shapes, thicknesses, and materials of auxetic materials to reduce the risk of injury.