Fiber Bragg grating based investigation of residual strains in ABS parts fabricated by fused deposition modeling process

Kantaros, Antreas; Karalekas, D.

doi:10.1016/j.matdes.2013.02.067

Cited by 175 publications

(82 citation statements)

References 30 publications

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“…These stresses are generated in the material due to the temperature gradient and contraction that are produced during the process. Kantaros & Karalekas (2013) studied the influence of layer thickness and printing orientation on the residual strain, concluding that the residual strain is minimal when using a longitudinal orientation (0º) and a layer thickness of 0,25 mm.…”

Section: State Of the Artmentioning

confidence: 99%

Investigating the influence of infill percentage on the mechanical properties of fused deposition modelled ABS parts

2016

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ABSTRACT3D printing is a manufacturing process that is usually used for modeling and prototyping. One of the most popular printing techniques is fused deposition modeling (FDM), which is based on adding melted material layer by layer. Although FDM has several advantages with respect to other manufacturing materials, there are several problems that have to be faced. When setting the printing options, several parameters have to be taken into account, such as temperature, speed, infill percentage, etc. Selecting these parameters is often a great challenge for the user, and is generally solved by experience without considering the influence of variations in the parameters on the mechanical properties of the printed parts.This article analyzes the influence of the infill percentage on the mechanical properties of ABS (Acrylonitrile Butadiene Styrene) printed parts. In order to characterize this influence, test specimens for tensile strength and Charpy tests were printed with a Makerbot Replicator 2X printer, in which the infill percentage was varied but the rest of the printing parameters were kept constant. Three different results were analyzed for these tests: tensile strength, impact resistance, and effective printing time. Results showed that the maximum tensile force (1438 N) and tensile stress (34,57 MPa) were obtained by using 100 % infill. The maximum impact resistance, 1,55 J, was also obtained with 100 % infill. In terms of effective printing time, results showed that printing with an infill range between 50 % and 98 % is not recommended, since the effective printing time is higher than with a 100 % infill and the tensile strength and impact resistance are smaller. In addition, in comparing the results of our analysis with results from other authors, it can be concluded that the printer type and plastic roll significantly influence the mechanical properties of ABS parts.Keywords: 3D printing, mechanical properties, FDM process, ABS, makerbot replicator 2X. RESUMENLa impresión 3D es un proceso de manufactura que se basa en la fabricación de prototipos, partes y piezas funcionales. Existen diferentes métodos, en los cuales se utilizan distintos materiales en diversos formatos. Uno de los métodos más utilizados es el modelado por deposición fundida (FDM). A pesar de las ventajas que posee con respecto a otros procesos de fabricación, la impresión 3D no está libre de dificultades o problemas. Al momento de configurar una impresión, se deben ingresar parámetros para cada una de las variables presentes en el proceso, como por ejemplo: temperatura, velocidad, porcentaje de relleno, etc. La elección de dichos parámetros muchas veces resulta ser un problema para el operador, y generalmente se realiza en función de su experiencia, sin considerar la influencia que estos parámetros tendrán en las propiedades mecánicas del elemento terminado. Este trabajo analiza la influencia del porcentaje de relleno en la resistencia mecánica de piezas fabricadas en ABS (Acrilonitrilo Butadieno Estireno). Para ello, se imprimieron pr...

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Section: State Of the Artmentioning

confidence: 99%

Investigating the influence of infill percentage on the mechanical properties of fused deposition modelled ABS parts

2016

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“…Given the limitations, researchers also employed experiment-based empirical modeling approaches [14,28,38,[45][46][47]. Sensing techniques have also been used to ensure the quality of FDM built parts [11,27,40,41].…”

Section: Machine Condition and Process Monitoringmentioning

confidence: 99%

In situ monitoring of FDM machine condition via acoustic emission

Hai-xi

Wang

2015

Int J Adv Manuf Technol

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Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for fabricating prototypes with complex geometry and different materials. However, current commercial FDM machines have the limitations in process reliability and product quality. In order to overcome these limitations and increase the levels of machine intelligence and automation, machine conditions need to be monitored more closely as in closedloop control systems. In this study, a new method for in situ monitoring of FDM machine conditions is proposed, where acoustic emission (AE) technique is applied. The proposed method allows for the identification of both normal and abnormal states of the machine conditions. The time-domain features of AE hits are used as the indicators. Support vector machines with the radial basis function kernel are applied for state identification. Experimental results show that this new method can potentially serve as a nonintrusive diagnostic and prognostic tool for FDM machine maintenance and process control.

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“…[1][2][3][4][5][6][7][8][9][10] Rapid prototyping can shape such raw materials as ceramic, metal and plastic, as well as cells and tissues. [11] The methods used for rapid prototyping include Fused Deposition Modeling (FDM), [12] Stereolithography (STL), [13] Selective Laser Sintering (SLS), [14] and Laminated Object Manufacturing (LOM). [15] In FDM, an extrusion nozzle is used to heat and melt the material that is then deposited in layers.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on the 3D‐printed plastic parts and predicting the mechanical properties using artificial neural networks

Bayraktar

Uzun

Çakıroğlu

et al. 2016

Polymers for Advanced Techs

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This study investigates the mechanical properties of 3D‐printed plastic parts fabricated using Fused Deposition Modeling (FDM). For this purpose, a 3D printer named KASAME was designed and built by the researchers. The test samples were fabricated using polylactic acid (PLA). The experiments were conducted using three melt temperatures (190°C, 205°C, and 220°C), four layer thickness values (0.06 mm, 0.10 mm, 0.19 mm, and 0.35 mm), and three raster pattern orientations (+45°/−45° [the crisscross pattern], horizontal and vertical). Tensile strength tests were performed to determine tensile strength values of the samples and fracture surfaces were also analyzed. Using artificial neural networks, a mathematical model for the tensile test results was generated corresponding to the raster pattern employed in 3D fabrication. Tensile strength tests indicated that melt temperature, layer thickness, and raster pattern orientation had a significant effect on the tensile strengths of the samples. According to the result of the experiment, the maximum average tensile strength values were observed for the samples fabricated using the crisscross raster pattern. The analysis of variance (ANOVA) table shows the raster pattern (PCR) value of 48.68% was obtained with the highest degree of influence. With respect to R2, the best performing artificial neural network model, with test and training values of 0.999199 and 0.999997, respectively, was observed to be the crisscross raster pattern. Copyright © 2016 John Wiley & Sons, Ltd.

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Fiber Bragg grating based investigation of residual strains in ABS parts fabricated by fused deposition modeling process

Cited by 175 publications

References 30 publications

Investigating the influence of infill percentage on the mechanical properties of fused deposition modelled ABS parts

Investigating the influence of infill percentage on the mechanical properties of fused deposition modelled ABS parts

In situ monitoring of FDM machine condition via acoustic emission

Experimental study on the 3D‐printed plastic parts and predicting the mechanical properties using artificial neural networks

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