Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method

Liu, Xinhua; Zhang, Mingshan; Li, Shengpeng; Si, Lina; Peng, Junquan; Yuan, Hu

doi:10.1007/s00170-016-9263-3

Cited by 125 publications

(65 citation statements)

References 21 publications

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“…Stratasys was one of the first companies to develop the FDM process and FDM machine. The following is a list of commonly used FDM machines: Fortus FDM 400 mc machine (Stratasys, Eden Prairie, MN, USA) [10,21,22], Fortus 360 mc machine (Stratasys, Eden Prairie, MN, USA) [23], FDM 200 mc machine (Stratasys, Eden Prairie, MN, USA) [24], FDM 1650 machine (Stratasys, Eden Prairie, MN, USA) [25][26][27][28], FDM Vantage machine (Stratasys, Eden Prairie, MN, USA) [29,30], Ultimaker 2 (Ultimaker, Amsterdam, Netherlands) [23,31,32], MakerBot Replicator 2 (MakerBot, New York, NY, USA) [33,34], MEM-300 machine (Beijing Yinhua Laser Rapid Prototypes Making and Mould Technology Co., Ltd, Beijing, China) [35], Uprint SE 3D printer (Stratasys, Eden Prairie, MN, USA) [5], The FDM 3000 3D printer (Stratasys, Eden Prairie, MN, USA) [36,37], Raise3D N2plus machine (Raise3D, Irvine, CA, USA) [38], Makerbot Replicator 2X (MakerBot, New York, NY, USA) [1,3,20], Julia 3D printer (Fracktal Works, Bangalore, India) [7], FDM Maxum Machine (Stratasys, Eden Prairie, MN, USA) [39], Prodigy Plus (Stratasys, Eden Prairie, MN, USA) [6,40], WitBox desktop 3D printer (BQ, Madrid, Spain) [11], and HP Designjet 3D CQ656A (HP, Palo Alto, CA, USA) [41].…”

Section: Fdm Equipmentmentioning

confidence: 99%

“…Among the six parameters, build orientation, layer thickness, infill density, and extrusion temperature were significant for tensile properties (Young's modulus, tensile strength, yield strength). Liu et al [33] analyzed layer thickness, build orientation, raster orientation, raster width, and air gap and determined an optimum combination of process parameters for the tensile properties. The authors designed parts for the tensile test and the experiment according to GB/T 1040.2-2006 (Chinese Standard) and a Taguchi orthogonal array, respectively.…”

Section: Tensile Strengthmentioning

confidence: 99%

“…Parts were produced according to ASTM D790 from ABS P430 filament, and the results indicated that flexural properties, like compressive properties, were maximum at 0 • build orientation. Liu et al [33] designed their experiments based on a Taguchi orthogonal array, and PLA parts were designed according to GB/T 9341 (a Chinese testing standard). According to ANOVA analysis at a 5% significance level, they concluded that build orientation, layer thickness, and raster orientation were significant for flexural strength.…”

Section: Flexural Strengthmentioning

confidence: 99%

“…In addition, the author also employed an ANN approach for prediction. Liu et al [33] also applied the Taguchi method for evaluating the levels of process parameters (build orientation, layer thickness, raster orientation, raster width, and raster gap) for tensile strength, flexural strength, and impact strength.…”

Section: Process Parameter Optimizationmentioning

confidence: 99%

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A Systematic Survey of FDM Process Parameter Optimization and Their Influence on Part Characteristics

Dey

Yodo

2019

JMMP

331

257

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Fused deposition modeling (FDM) is an additive manufacturing (AM) process that is often used to fabricate geometrically complex shaped prototypes and parts. It is gaining popularity as it reduces cycle time for product development without the need for expensive tools. However, the commercialization of FDM technology in various industrial applications is currently limited due to several shortcomings, such as insufficient mechanical properties, poor surface quality, and low dimensional accuracy. The qualities of FDM-produced products are affected by various process parameters, for example, layer thickness, build orientation, raster width, or print speed. The setting of 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 various parameters. The optimum setting of parameters is deemed to improve the qualities of three-dimensional (3D) printed parts and may reduce post-production work. This paper intensively reviews state-of-the-art literature on the influence of parameters on part qualities and the existing work on process parameter optimization. Additionally, the shortcomings of existing works are identified, challenges and opportunities to work in this field are evaluated, and directions for future research in this field are suggested.

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Section: Fdm Equipmentmentioning

confidence: 99%

Section: Tensile Strengthmentioning

confidence: 99%

Section: Flexural Strengthmentioning

confidence: 99%

Section: Process Parameter Optimizationmentioning

confidence: 99%

See 2 more Smart Citations

A Systematic Survey of FDM Process Parameter Optimization and Their Influence on Part Characteristics

Dey

Yodo

2019

JMMP

331

257

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“…Recently, novel manufacturing methods are enabled to solve many long-term processes, such as molding and casting [5]. Additive manufacturing (AM) has been introduced for tackling this problem with many applications for creating samples with high accuracy [6]. One of the most significant approaches of AM methods is fused deposition modeling (FDM), which can create samples by 3D printing technology ( Figure 1) [7].…”

Section: Introductionmentioning

confidence: 99%

The Synergic Effects of FDM 3D Printing Parameters on Mechanical Behaviors of Bronze Poly Lactic Acid Composites

et al. 2020

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In this paper, the influence of layer thickness (LT), infill percentage (IP), and extruder temperature (ET) on the maximum failure load, thickness, and build time of bronze polylactic acid (Br-PLA) composites 3D printed by the fused deposition modeling (FDM) was investigated via an optimization method. PLA is a thermoplastic aliphatic polyester obtained from renewable sources, such as fermented plant starch, especially made by corn starch. The design of experiment (DOE) approach was used for optimization parameters, and 3D printings were optimized according to the applied statistical analyses to reach the best features. The maximum value of failure load and minimum value of the build time were considered as optimization criteria. Analysis of variance results identified the layer thickness as the main controlled variable for all responses. Optimum solutions were examined by experimental preparation to assess the efficiency of the optimization method. There was a superb compromise among experimental outcomes and predictions of the response surface method, confirming the reliability of predictive models. The optimum setting for fulfilling the first criterion could result in a sample with more than 1021 N maximum failure load. Finally, a comparison of maximum failure from PLA with Br-PLA was studied.

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4D Printing of Shape Memory Polymers, Blends, and Composites and Their Advanced Applications: A Comprehensive Literature Review

et al. 2022

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4D printing is defined as the additive manufacturing process of smart (stimuli‐responsive) materials. Shape memory materials are sensitive to specific stimuli such as heat, electricity, magnetic fields, etc., which can change their form or properties. This characteristic gives the material a dynamic behavior over time (the fourth dimension). The application of the 4D printing technique is currently being explored in various fields, including soft robotics, electrical devices, deployable structures, medical implants, and medicine delivery systems. This article first examines the fundamentals of 3D printing techniques, their advantages, and limitations. Then, the shape memory materials are categorized and reviewed according to their type (shape memory polymers, shape memory composites, polymer blends, etc.) and stimulus responsiveness. Finally, different properties of shape memory materials like shape memory effect, thermomechanical properties, and their compatibility with different types of additive manufacturing processes are discussed.

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Mechanical property parametric appraisal of fused deposition modeling parts based on the gray Taguchi method

Cited by 125 publications

References 21 publications

A Systematic Survey of FDM Process Parameter Optimization and Their Influence on Part Characteristics

A Systematic Survey of FDM Process Parameter Optimization and Their Influence on Part Characteristics

The Synergic Effects of FDM 3D Printing Parameters on Mechanical Behaviors of Bronze Poly Lactic Acid Composites

4D Printing of Shape Memory Polymers, Blends, and Composites and Their Advanced Applications: A Comprehensive Literature Review

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