Woven Carbon Fiber Reinforced Laminate Matrix Composite Through Fused Deposition Modeling

Author(s):  
Rachit Ranjan ◽  
Piyush Raote ◽  
Vivek Bajpai

Abstract A novel fused deposition modeling (FDM) based fabrication technique for Woven carbon fiber (WCF) reinforced PLA matrix laminated composite was proposed. The composite was fabricated by placing a layer of carbon fiber (CF) after every 5th layer of PLA matrix such that there was a total of 3 layers of CF in every tensile specimen fabricated. The parameter such as extrusion temperature, feed rate, and bed temperature was initially optimized by the Taguchi L9 optimization technique to get high-density low surface roughness specimens. Mechanical properties such as tensile strength and flexural strength of the specimen were measured in Hounsfield tensile testing machine. The composite has the yield and ultimate tensile strength of 43.378 MPa and 70.84 MPa which is 114.01% and 172.94% higher than the unreinforced specimen. The Flexural strength of the composite was found to be 117.88 MPa which is 17.91 % higher than the unreinforced 3D printed specimen. The proposed technique has offered a potential strategy to fabricate low-cost products with variable design for versatile applications such as aerospace and automobile industries.

2020 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Arivazhagan Selvam ◽  
Suresh Mayilswamy ◽  
Ruban Whenish ◽  
Rajkumar Velu ◽  
Bharath Subramanian

The most common method to fabricate both simple and complex structures in the additive manufacturing process is fused deposition modeling (FDM). Many researchers have studied the strengthening of FDM components by adding short carbon fibers (CF) or by reinforcing solid carbon fiber rods. In the current research, we sought to enhance the mechanical properties of FDM components by adding bioinspired solid CF rods during the fabrication process. An effective bonding interface of bioinspired CF rods and polylactic acid (PLA) was achieved by triangular interlocking sutures and by employing synthetic glue as the binding agent. In particular, the tensile strength of solid CF rod reinforced PLA samples was studied. Critical parameters such as layer thickness, extruder temperature, extruder speed, and shell thickness were considered for optimization. Significant process parameters were identified through leverage plots using the response surface methodology (RSM). The optimum parameters were found to be layer thickness of 0.04 mm, extruder temperature of 215 °C, extruder speed of 60 mm/s, and shell thickness of 1.2 mm. The results revealed that the bioinspired solid CF rod reinforced PLA (CFRPLA) composite exhibited a tensile strength of 82.06 MPa, which was approximately three times higher than the pure PLA (28 MPa, 66% lower than CFRPLA), acrylonitrile butadiene styrene (ABS) (28 MPa, 66% lower than CFRPLA), polyethylene terephthalate glycol (PETG) (34 MPa, 60% lower than CFRPLA), and nylon (34 MPa, 60% lower than CFRPLA) samples.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Debashis Mishra ◽  
Anil Kumar Das

PurposeThe purpose of the experimental investigation was to optimize the process parameters of the fused deposition modeling (FDM) technique. The optimization of the process was performed to identify the relationship between the chosen factors and the tensile strength of acrylonitrile butadiene styrene (ABS) and carbon fiber polylactic acid (PLA) thermoplastic material, FDM printed specimens. The relationship was demonstrated by using the linear experimental model analysis, and a prediction expression was established. The developed prediction expression can be used for the prediction of tensile strength of selected thermoplastic materials at a 95% confidence level.Design/methodology/approachThe Taguchi L9 experimental methodology was used to plan the total number of experiments to be performed. The process parameters were chosen as three at three working levels. The working range of chosen factors was the printing speed (60, 80 and 100mm/min), 40%, 60% and 80% as the infill density and 0.1mm, 0.2mm and 0.3mm as the layer thickness. The fused deposition modeling process parameters were optimized to get the maximum tensile strength in FDM printed ABS and carbon fiber PLA thermoplastic material specimens.FindingsThe optimum condition was achieved by the process optimization, and the desired results were obtained. The maximum desirability was achieved as 0.98 (98%) for the factors, printing speed 100mm/min, infill density 60mm and layer thickness 0.3mm. The strength of the ABS specimen was predicted to be 23.83MPa. The observed strength value was 23.66MPa. The maximum desirability was obtained as 1 (100%) for the factors, printing speed 100mm/min, infill density 60mm and layer thickness 0.2mm. The strength of the carbon fiber PLA specimen was predicted to be 26.23MPa, and the obtained value was 26.49MPa.Research limitations/implicationsThe research shows the useful process parameters and their suitable working conditions to print the tensile specimens of the ABS and carbon fiber PLA thermoplastics by using the fused deposition modeling technique. The process was optimized to identify the most influential factor, and the desired optimum condition was achieved at which the maximum tensile strength was reported. The produced prediction expression can be used to predict the tensile strength of ABS and carbon fiber PLA filaments.Practical implicationsThe results obtained from the experimental investigation are useful to get an insight into the FDM process and working limits to print the parts by using the ABS and carbon fiber PLA material for various industrial and structural applications.Social implicationsThe results will be useful in choosing the suitable thermoplastic filament for the various prototyping and structural applications. The products that require freedom in design and are difficult to produce by most of the conventional techniques can be produced at low cost and in less time by the fused deposition modeling technique.Originality/valueThe process optimization shows the practical exposures to state an optimum working condition to print the ABS and carbon fiber PLA tensile specimens by using the FDM technique. The carbon fiber PLA shows better strength than ABS thermoplastic material.


2020 ◽  
Vol 870 ◽  
pp. 73-80
Author(s):  
Nuha Hadi Jasim Al Hasan

3D printing innovation, as a quick prototyping, utilize plastic or metal as the crude material to print the genuine parts layer by layer. In this way, it is likewise called added substance producing procedure. Contrasted and conventional assembling innovation, 3D printing innovation has evident points of interest in assembling items with complex shapes and structures. Fused deposition modeling (FDM) is one of the most broadly utilized 3D printing advances. Fibers of thermoplastic materials, for example, polylactic acid is for the most part utilized as crude materials. The present examination will concentrate on the effect of the infill density, percent on the flexural strength of polylactic acid. Bending test was performed on different infill density, percent of specimens. According to ASTM D638.14 standards, samples for testing are made in different infill density, percent (20, 30, 40, 50 and 60 %) by using a polylactic acid in 3D machine printing and their tensile tested and the parameters include different fill density, layer high of 0.1 mm , 0.2mm and 0.3 have an effect on the mechanical characterized while the time of printing the sample would be increased with increasing of fill density%. The tensile strength of polylactic acid samples was found at different fill density and a layer thickness. According to test measuring results that the tensile strength, maximum 47.1,47.4, and 48 MPa at 30%,40%,and 50% fill density respectively and 0.1mm height layer and the tensile strength minimum at 60% and 70 % fill density and 0.1 mm height layer thickness. The higher strength results as higher layer thickness 0.3 mm as compared with 0.1 and 0.2 at 30%fill density.


2021 ◽  
pp. 251659842110311
Author(s):  
Shrikrishna Pawar ◽  
Dhananjay Dolas1

Fused deposition modeling (FDM) is one of the most commonly used additive manufacturing (AM) technologies, which has found application in industries to meet the challenges of design modifications without significant cost increase and time delays. Process parameters largely affect the quality characteristics of AM parts, such as mechanical strength and surface finish. This article aims to optimize the parameters for enhancing flexural strength and surface finish of FDM parts. A total of 18 test specimens of polycarbonate (PC)-ABS (acrylonitrile–butadiene–styrene) material are printed to analyze the effect of process parameters, viz. layer thickness, build orientation, and infill density on flexural strength and surface finish. Empirical models relating process parameters with responses have been developed by using response surface regression and further analyzed by analysis of variance. Main effect plots and interaction plots are drawn to study the individual and combined effect of process parameters on output variables. Response surface methodology was employed to predict the results of flexural strength 48.2910 MPa and surface roughness 3.5826 µm with an optimal setting of parameters of 0.14-mm layer thickness and 100% infill density along with horizontal build orientation. Experimental results confirm infill density and build orientation as highly significant parameters for impacting flexural strength and surface roughness, respectively.


2017 ◽  
Vol 23 (5) ◽  
pp. 943-953 ◽  
Author(s):  
Anthony A. D’Amico ◽  
Analise Debaie ◽  
Amy M. Peterson

Purpose The aim of this paper is to examine the impact of layer thickness on irreversible thermal expansion, residual stress and mechanical properties of additively manufactured parts. Design/methodology/approach Samples were printed at several layer thicknesses, and their irreversible thermal expansion, tensile strength and flexural strength were determined. Findings Irreversible thermal strain increases with decreasing layer thickness, up to 22 per cent strain. Tensile and flexural strengths exhibited a peak at a layer thickness of 200 μm although the maximum was not statistically significant at a 95 per cent confidence interval. Tensile strength was 54 to 97 per cent of reported values for injection molded acrylonitrile butadiene styrene (ABS) and 29 to 73 per cent of those reported for bulk ABS. Flexural strength was 18 to 41 per cent of reported flexural strength for bulk ABS. Practical implications The large irreversible thermal strain exhibited that corresponding residual stresses could lead to failure of additively manufactured parts over time. Additionally, the observed irreversible thermal strains could enable thermally responsive shape in additively manufactured parts. Variation in mechanical properties with layer thickness will also affect manufactured parts. Originality/value Tailorable irreversible thermal strain of this magnitude has not been previously reported for additively manufactured parts. This strain occurs in parts made with both high-end and consumer grade fused deposition modeling machines. Additionally, the impact of layer thickness on tensile and flexural properties of additively manufactured parts has received limited attention in the literature.


Author(s):  
Tran Linh Khuong ◽  
Zhao Gang ◽  
Muhammad Farid ◽  
Rao Yu ◽  
Zhuang Zhi Sun ◽  
...  

Biomimetic robots borrow their structure, senses and behavior from animals, such as humans or insects, and plants. Biomimetic design is design ofa machine, a robot or a system in engineeringdomain thatmimics operational and/orbehavioral model of a biological system in nature. 3D printing technology has another name as rapid prototyping technology. Currently it is being developed fastly and widely and is applied in many fields like the jewelry, footwear, industrial design, architecture, engineering and construction, automotive, aerospace, dental and medical industry, education, geographic information system, civil engineering, guns. 3D printing technology is able to manufacture complicated, sophisticated details that the traditional processing method cannot manufacture. Therefore, 3D printing technology can be seen as an effective tool in biomimetic, which can accurately simulate most of the biological structure. Fused Deposition Modeling (FDM) is a technology of the typical rapid prototyping. The main content of the article is the focusing on tensile strength test of the ABS-Acrylonitrile Butadiene Styrene material after using Fused Deposition Modeling (FDM) technology, concretization after it’s printed by UP2! 3D printer. The article focuses on two basic features which are Tensile Strength and Determination of flexural properties.


2015 ◽  
Vol 20 ◽  
pp. 243-248 ◽  
Author(s):  
Hua Wei Guan ◽  
Monica Mahesh Savalani ◽  
Ian Gibson ◽  
Olaf Diegel

2021 ◽  
Vol 349 ◽  
pp. 01008
Author(s):  
Nikolaos A. Fountas ◽  
Ioannis Papantoniou ◽  
John D. Kechagias ◽  
Dimitrios E. Manolakos ◽  
Nikolaos M. Vaxevanidis

The properties of fused deposition modeling (FDM) products exhibit strong dependence on process parameters which may be improved by setting suitable levels for parameters related to FDM. Anisotropic and brittle nature of 3D-printed components makes it essential to investigate the effect of FDM control parameters to different performance metrics related to resistance for improving strength of functional parts. In this work the flexural strength of polyethylene terephthalate glycol (PET-G) is examined under by altering the levels of different 3D-printing parameters such as layer height, infill density, deposition angle, printing speed and printing temperature. A response surface experiment was established having 27 experimental runs to obtain the results for flexural strength (MPa) and to further investigate the effect of each control parameter on the response by studying the results using statistical analysis. The experiments were conducted as per the ASTM D790 standard. The regression model generated for flexural strength adequately explains the variation of FDM control parameters on flexural strength and thus, it can be implemented to find optimal parameter settings with the use of either an intelligent algorithm, or neural network.


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