Raster Width Research Articles

Parametric Effects of Fused Filament Fabrication Approach on Surface Roughness of Acrylonitrile Butadiene Styrene and Nylon-6 Polymer.

This research objective is to optimize the surface roughness of Nylon-6 (PA-6) and Acrylonitrile Butadiene Styrene (ABS) by analyzing the parametric effects of the Fused Filament Fabrication (FFF) technique of Three-Dimensional Printing (3DP) parameters. This article discusses how to optimize the surface roughness using Taguchi analysis by the S/N ratio, ANOVA, and modeling methods. The effects of ABS parameters (initial line thickness, raster width, bed temperature, build pattern, extrusion temperature, print speed, and layer thickness) and PA-6 parameters (layer thickness, print speed, extrusion temperature, and build pattern) were investigated with the average surface roughness (Ra) and root-mean-square average surface roughness (Rq) as response parameters. Validation tests revealed that Ra and Rq decreased significantly. After the optimization, the Ra-ABS and Rq-PA-6 for the fabricated optimized values were 1.75 µm and 21.37 µm, respectively. Taguchi optimization of Ra-ABS, Rq-ABS, Ra-PA-6, and Rq-PA-6 was performed to make one step forward to use them in further research and prototypes.

Additively manufactured foamed polylactic acid for lightweight structures

PurposeThis study aims to make foamed polylactic acid (PLA) structures with different densities by varying deposition temperatures using the material extrusion (MEX) additive manufacturing process.Design/methodology/approachThe extrusion multiplier (EM) was calibrated for each deposition temperature to control foaming expansion. Material density was determined using extruded cubes with the optimal EM value for each deposition temperature. The influence of deposition temperature on the tensile, compression and flexure characteristics of the foamable filament was studied experimentally.FindingsThe foaming expansion ratio, the consistency of the raster width and the raster gap significantly affect the surface roughness of the printed samples. Regardless of the loading conditions, the maximum stiffness and yield strength were achieved at a deposition temperature of 200°C when the PLA specimens had no foam. When the maximum foaming occurred (220°C deposition temperature), the stiffness and yield strength of the PLA specimens were significantly reduced.Practical implicationsThe obvious benefit of using foamed materials is that they are lighter and consume less material than bulky polymers. Injection or compression moulding is the most commonly used method for creating foamed products. However, these technologies require tooling to fabricate complicated parts, which may be costly and time-consuming. Conversely, the MEX process can produce extremely complex parts with less tooling expense, reduction in energy use and optimised material consumption.Originality/valueThis study investigates the possibility of stiff, lightweight structures with low fractions of interconnected porosity using foamable filament.

The Influence of Operational Settings on the Tensile Strength of an FDM-Printed Abs Component

Abstract: This paper’s purpose is to investigate tensile strength of FDM-print ABS components. FDM has evolved beyond rapid prototyping to rapid manufacturing in recent years, allowing items manufactured using the FDM process to be used immediately. Poor and anisotropic mechanical qualities, on the other hand, had a substantial influence on the use of fused model manufactured components. By carefully selecting framework, the automated qualities often FDM components can be improved. There will be three parameters on which the research is going through, angle of raster, height of layer, and breadth of raster, were chosen in this work to investigate their impact in the tensile samples. The components are manufactured to the ASTM D638 Type 4 standard. The inflated tensile strength was found with a angle of raster of 0 degrees. Because of the larger bonding surface between the layers, a lower layer height is associated with better tensile strength. The strength of a tensile component improves up to a point when the raster width is increased, after which the existence of void diminishes and tells how strong a material is when it is stretched.

Characterization and parametric optimization of additive manufacturing process for enhancing mechanical properties

Additive manufacturing (AM), also known as 3D printing, is a cutting-edge industrial production technique that enables the creation of lighter, stronger components and systems. Fused deposition modeling (FDM) is a popular AM process for creating prototypes and functional components out of common engineering polymers. The mechanical characteristics of printed items are dramatically altered as a result of various process factors. As a result, it is critical to examine the impact of printing settings on the quality of the printed item. In terms of flexural strength, this study presents an experimental examination into the quality analysis of parameters on printed components utilizing FDM. By adjusting process factors such as layer height, raster width, raster angle, and orientation angle, the experiment was carried out utilizing Taguchi's L18 mixed orthogonal array approach. The UNITEK-94100 universal testing equipment was used to evaluate the flexural strength of Acrylonitrile butadiene styrene (ABS) specimens that had been conditioned as per ASTM D790 standard. The impacts of parameters on experimental results were examined and optimized using the hybrid genetic algorithm with response surface methods, response surface approach, and Taguchi method. When the optimal solutions of each technique were studied, the response surface approach and Taguchi methods were determined to be less promising than the genetic algorithm method.

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.

A Novel FDM Based Additive Manufacturing of PLA Components Using Optimized Deep Learning Strategy

Abstract: Fused Deposit modeling (FDM) is an additive manufacturing (AM) process that's frequently used to fabricate geometrically complex shaped prototypes and complex parts. It's gaining market as it reduces cycle time for product development without the need for high priced tools. Still, the commercialization of FDM technology in other artificial operations is presently limited due to several failings, alike as inadequate mechanical properties, poor surface quality, and low dimensional accuracy. The rates of FDM- produced products are affected by other process parameters, for illustration, layer thickness, build angle, raster width, or print speed. The process parameters and their range depends on the section of FDM machines. Filament materials, nozzle dimensions, and the type of machine determine the range of other parameters. The optimum setting of parameters is supposed to ameliorate the rates of three-dimensional (3D) printed specimens and may reducepost-production work. This paper intensely reviews state-of-the- art literature on the influence of parameters on part qualities and the being work on process parameter optimization. Also, the failings of being workshop are linked, challenges and openings to work in this field are estimated, and directions for future research and development in this field are suggested Keywords: Fused deposition modelling; process parameters; part characteristics; optimization

Real-time monitoring of raster temperature distribution and width anomalies in fused filament fabrication process

Real-time monitoring of raster temperature distribution and width anomalies in fused filament fabrication process

Prediction of tensile strength of fused deposition modeling (FDM) printed PLA using classic laminate theory

The application of Fused Deposition Modeling (FDM) is restricted due to limited information about the mechanical properties of printed parts. Therefore, it is required to determine the mechanical properties of the FDM properties to avail the full benefit of the FDM process. In the present study, Classic Laminate Theory (CLT) has been employed at the different configurations of layer thickness and raster width. The required elastic constant of material for CLT has been experimentally obtained through FDM printed Polylactic Acid (PLA) unidirectional specimens at 0°, 45° and 90° for different combinations of layer height and raster width. For these different combinations of layer height and raster width, constitutive models were developed to predict the tensile properties of the PLA parts. Tensile strength of the FDM printed bi-directional specimens has been experimentally obtained to validate the proposed CLT model results. The experimental tensile strength data is in good agreement with the data predicted by the proposed CLT model. Higher tensile strength and modulus were achieved with 0° raster angle compared to 90° raster angle. In the case of a bi-directional printed specimen, higher tensile strength was obtained with 45°/-45° raster angle followed by 30°/-60° and 0°/90° raster angle.

Modeling and analysis of flexural strength with fuzzy logic technique for a fused deposition modeling ABS components

Fused Deposition Modeling (FDM) is an additive manufacturing technique used for prototype, physical modeling, and end-of-line production. Proper parameter selection is essential for producing high-quality items with suitable mechanical properties, such as flexural strength. Four critical process variables, such as layer thickness, raster width, raster angle, and orientation angle, are investigated in this study. The link between these factors and the flexural strength of the Acrylonitrile Butadiene Styrene (ABS) printed components are analysed using analysis of variance. The fuzzy logic (FL) approaches were used to develop a prediction model. The test samples are made on a 3D forge dreamer II printing machine of the FDM type. In Minitab software, the Taguchi mixed L18 orthogonal design technique was used to organize the trials. The result showed that the raster angle has the most significant parameter affecting flexural strength when compere with layer thickness, raster width and orientation angle. The fuzzy logic models provided high accuracy prediction of flexural strength with the maximum percentage error of 3.62%, and this revealed that the model and the experimental data were in good agreement.

Parametric optimization of FDM using the ANN-based whale optimization algorithm

AbstractSurface roughness (SR) is one of the major parameters used to govern the quality of the fused deposition modeling (FDM)-printed products, and the FDM process parameters can be easily regulated in order to obtain a good surface finish. The surface quality of the product produced by the FDM is generally affected by the staircase effect that needs to be managed. Also, the production time (PT) to fabricate the product and volume percentage error (VPE) should be minimized to make the FDM process more efficient. The aim of this paper is to accomplish these three objectives with the use of the parametric optimization technique integrating the artificial neural network (ANN) and the whale optimization algorithm (WOA). The FDM parameters which have been taken into consideration are layer thickness, nozzle temperature, printing speed, and raster width. Experimentation has been conducted on printed samples to examine the impact of the input parameters on SR, VPE, and PT according to Taguchi's L27 orthogonal array. The ANN model has been built up using the experimental data, which was further used as an objective function in the WOA with an aim to minimize output responses. The robustness of the proposed method has been validated on the optimal combinations of FDM process parameters.

Analysis of the effect of the process parameters on the mechanical strength of 3D printed and adhesively bonded PETG single lap joint

The current study deals with the effect of 3D printing parameters on the strength of 3d printed and adhesively bonded PETG single lap joints. Polyethylene terephthalate glycol (PETG) is used to print standard specimens with different printing parameters (raster angle, raster width, and layer thickness) using fused deposition modelling (FDM) process. By conducting number of tensile tests on the single lap joint specimens, the effect of abovementioned 3D printing parameters on the mechanical behaviour of PETG joints is determined. Furthermore, a computational investigation was carried out to confirm the experimental results and gain a better understanding of the fracture behaviour of these types of joints. The effect of above mentioned 3D printing parameters in stress distribution and failure behaviour of the joints are examined and reported. Taking into Consideration of a growing interest in FDM 3D printing technology in manufacturing and many other applications of adhesively bonded joints, obtained results are useful for future studies on new designs of 3D printed adhesively bonded products with a greater strength and improved structural performance.

Optimisation of tensile and compressive behaviour of PLA 3D printed parts using categorical response surface methodology

The present study aims to optimise process parameters of 3-D printed polylactic acid (PLA) part using response surface methodology (RSM). The input printing process parameters considered are layer height (L), infill percentage (I), raster width (R) and infill patterns (P) (i.e., linear, hexagonal and diamond), while the responses are tensile and compressive strengths. Box Behnken array design is applied for experimental runs and also to fit quadratic regression models. The results revealed that significant parameters affecting compression strength performance are I, I2, R, and interaction of I and R, for tensile strength, are L, I, I2, R, P, and interaction of P with L and I. The simultaneously optimised parameters obtained based on composite desirability function for compression and tensile strength are L = 0.1 mm, I = 100%, R = 0.4 mm, and P = hexagonal, while the obtained maximum compression and tensile strength are 9.06 kN and 1.67 kN.

RSM based investigation of compressive properties of FDM fabricated part

This study investigates the performance of the acrylonitrile-butadiene-styrene (ABS) P400 part, manufactured using fused deposition modeling (FDM), under compressive loading. Effect of varying levels of three FDM process parameters, i.e., raster angle (A), air gap (B), and raster width (C) on three responses, namely compressive stress (CS), percentage deformation (% D), and breaking stress (BS) of the fabricated parts is studied. Experimental results are analysed using analysis of variance (ANOVA), response graphs, and 3D surface plots. Investigations established the anisotropic nature of the ABSP400 part, which causes lower strength of the fabricated parts. Chosen process parameters significantly affect the compressive properties. A complex relationship exists between process parameters and the studied responses. It is also observed that BS is much lower than CS and % D varies in a contradictory fashion with changes in process parameters. Predictive models for the responses are developed and validated through additivity tests. To discover the best combination of FDM process parameters for optimum responses, multi-objective optimization utilizing the desirability function approach is used. Multi-objective optimization results are validated using the confirmatory test. The novelty of the present work is that it explores the effect of three critical parameters of the FDM process not only on compressive stress (CS) but also on other critical compressive properties such as percentage deformation (% D) and breaking stress (BS) of the ABS P400 fabricated parts.

Fracture and structural performance of adhesively bonded 3D-printed PETG single lap joints under different printing parameters

The present study, deals with fracture behavior of adhesively bonded 3D-printed joints. Polyethylene terephthalate glycol (PETG) is used to print standard specimens with different printing parameters (raster angle, raster width, and layer thickness) using fused deposition modeling (FDM) process. Moreover, adhesive layer with different thicknesses is employed to determine effects of adhesive layer thickness on the structural integrity of 3D-printed joints. By a series of tensile tests on the single lap joint specimens, influence of above-mentioned 3D printing parameters on the mechanical behavior of PETG joints is determined. Moreover, numerical study was conducted to verify experimental results and provide enhanced knowledge on fracture behavior of these types of joints. The nonlinear 3D finite element model of the joint supports mechanical characteristics of both 3D-printed adherends and adhesive materials. The effect of above mentioned 3D printing parameters in stress distribution and failure behavior of the joints are examined and reported. Considering a growing interest in FDM 3D printing technology in manufacturing and numerous applications of adhesively bonded joints, reported results are beneficial for future developments of new designs of 3D printed adhesively bonded products with a higher strength and better structural performance.

Research on the Fused Deposition Modeling of Polyether Ether Ketone.

As a special engineering polymer, polyether ether ketone (PEEK) has been used widely due to its excellent mechanical properties, high thermal stability, and chemical resistance. Fused deposition modeling (FDM) is a promising process for fabricating PEEK parts. However, due to the semi-crystalline property and high melting point of PEEK, determining appropriate process parameters is important to reduce warpage deformation and improve the mechanical properties of PEEK. In this article, the influence of raster angle and infill density was determined by single factor experiment, which are the two most important parameters. The results showed that samples with 0°/90° raster angle and 50% infill density had the best comprehensive properties in terms of warpage deformation, tensile strength, and specific strength. Subsequently, based on the results above, the effects of printing speed, nozzle temperature, platform temperature, raster width, and layer thickness were analyzed by orthogonal experiment. The results indicated that platform temperature had the greatest impact on warpage deformation while printing speed and nozzle temperature were significant parameters on tensile strength. Through optimization, warpage deformation of the samples could be reduced to almost 0 and tensile strength could increase by 19.6% (from 40.56 to 48.50 MPa). This will support the development of FDM for PEEK.

Parametric optimization of parameters affecting dimension precision of FDM printed part using hybrid Taguchi-MARCOS-nature inspired heuristic optimization technique

Fused Deposition Modelling is a fast emerging technology due to its capacity to generate usable components with multiple geometrical designs in a fair period of time without the usage of any tooling or human interaction. The features and reliability of FDM fabricated parts are highly dependent on a small number of processing variables and their settings. The current study examines the relationship between five significant processing constraints. i.e. raster angle, part orientation, air gap, layer thickness and raster width and what effect do they have on the dimensional accuracy of the fabricated part. Twenty-seven experiments were piloted and configured using Taguchi’s architecture and recently formulated MARCOS Method. Here, the Genetic Algorithm Optimization, Simulated Annealing Algorithm Optimization, Particle Swarm Optimization, Grey-Wolf Optimization Algorithm, Moth Flame Optimization Algorithm, Whale Optimization Algorithm, Jaya Algorithm Optimization, Sunflower Optimization Algorithm, Lichtenberg Algorithm Optimization and Forensic Based Investigation Optimization approaches as ten different optimizations have been utilized to predict the optimal setting of the experiment. A comparative inspection of these nature-inspired algorithms in FDM printed part was performed in this study which reported part orientation as the most significant element.

Optimization of process parameters in fused deposition modelling of thermoplastics: A review

AbstractAmong the several techniques for additive manufacturing (AM), fused deposition modelling (FDM) is widely used. Fused deposition modelling process uses a thermoplastic material, which is melted and then extruded layer by layer through a nozzle, in order to create a three‐dimensional object. As a result of the default setting of process parameters provided by the manufacturers, produced parts normally have a poor surface finish, low mechanical properties, low dimensional accuracy, and increased residual stresses compared to the parts produced using conventional manufacturing processes like molding (casting). Qualities of fused deposition modelled (FDMed) parts are generally affected by process parameters including the layer thickness, extrusion temperature, build orientation, printing speed, raster angle, infill density, raster width, nozzle diameter, and air gap. Increasing infill density, printing temperature, and decreasing print speed and layer thickness lead to increase mechanical strength and improve the surface finish of the printed parts. The optimal process parameters are preferred to achieve superior properties of the parts. This paper reviews the optimal fused deposition modelling process parameters on part qualities for making the stability of used deposition modelled parts for use. Various process parameters are identified in order to obtain desirable qualities in the manufactured parts. Areas for future research are proposed.

Effect of nozzle diameter on mechanical and geometric performance of 3D printed carbon fibre-reinforced composites manufactured by fused filament fabrication

PurposeFused filament fabrication (FFF) is one of the most popular additive manufacturing (AM) technologies due to its ability to build thermoplastic parts with complex geometries at low cost. The FFF technique has been mainly used for rapid prototyping owing to the poor mechanical and geometrical properties of pure thermoplastic parts. However, both the development of new fibre-reinforced filaments with improved mechanical properties, and more accurate composite 3D printers have broadened the scope of FFF applications to functional components. FFF is a complex process with a large number of parameters influencing product quality and mechanical properties, and the effects of the combined parameters are usually difficult to evaluate. An array of parameter combinations has been analysed for improving the mechanical performance of thermoplastic parts such as layer thickness, build orientation, raster angle, raster width, air gap, infill density and pattern, fibre volume fraction, fibre layer location, fibre orientation and feed rate. This study aims to assess the effects of nozzle diameter on the mechanical performance and the geometric properties of 3D printed short carbon fibre-reinforced composites processed by the FFF technique.Design methodology approachTensile and three-point bending tests were performed to characterise the mechanical response of the 3D printed composite samples. The dimensional accuracy, the flatness error and surface roughness of the printed specimens were also evaluated. Moreover, manufacturing costs, which are related to printing time, were evaluated. Finally, scanning electron microscopy images of the printed samples were analysed to estimate the porosity as a function of the nozzle diameter and to justify the effect of nozzle diameter on dimensional accuracy and surface roughness.FindingsThe effect of nozzle diameter on the mechanical and geometric quality of 3D printed composite samples was significant. In addition, large nozzle diameters tended to increase mechanical performance and enhance surface roughness, with a reduction in manufacturing costs. In contrast, 3D printed composite samples with small nozzle diameter exhibited higher geometric accuracy. However, the effect of nozzle diameter on the flatness error and surface roughness was of slight significance. Finally, some print guidelines are included.Originality valueThe effect of nozzle diameter, which is directly related to product quality and manufacturing costs, has not been extensively studied. The presented study provides more information regarding the dependence of the mechanical, microstructural and geometric properties of short carbon fibre-reinforced nylon composite components on nozzle diameter.

Analysis of dimensional quality in 3D printed polylactic acid parts fabricated by fused deposition modeling

Fused deposition modeling (FDM) is an important 3D printing technique which extrudes thermoplastic polymer through a temperature controlled nozzle and deposits layer by layer over a solid platform to create three dimensional products. As each layer of the developed part is comprised of many rasters placed side by side, the part dimensional quality is directly affected by the accuracy of rasters. In the present study, Polylactic acid (PLA) specimens were printed using FDM 3D printer at nozzle temperatures 190 o C, 210 o C, and 230 °C. The part dimensions were measured using micrometer (Mitutoyo, Japan) while raster width and raster to raster air gap was visualized using SEM microscopy and ImageJ software tool. After analysis of the obtained results, it is observed that the minimum deviation in X and Y-dimensions is achieved at higher nozzle temperature; whereas minimum deviation in Z-dimension is obtained at a moderate nozzle temperature. Moreover, the effect of nozzle temperature on Y-dimension and Z-dimension (at shell) is almost similar. A positive deviation in raster width is observed at lower nozzle temperature and vice-versa. The effect of nozzle temperature on the raster to raster air gap was also significant and found maximum at nozzle temperature of 230 °C.

Impact of processing parameters on fatigue life of fused filament fabricated parts: application of central composite design and genetic algorithm tools

Generally, components tend to fail due to cyclic loading; therefore study of fatigue life of products is a critical issue. The purpose of this study is to develop a predictive model relating the process parameters with fatigue life of fused filament fabrication (FFF) technology-based 3D-printed parts. Test specimens are printed using a desktop FFF 3D printer to suit a laboratory-based fatigue testing machine. Response surface methodology-based central composite design method was used for the design of experiments to obtain a regression model for prediction of response. Lastly, genetic algorithm solver was used to optimise the predictive model results. Number of contours, layer thickness and raster width were found to have a significant effect while raster angle had very little effect on the fatigue life of FFF-based 3D printed parts. In addition, it was observed that there is a high significant interaction between layer thickness and raster width of the FFF specimens.