scholarly journals A New Specimen Geometry for Evaluation of the Mechanical Orthotropic Properties Presented in Parts Printed by FDM

2021 ◽  
Vol 9 (12) ◽  
pp. 1741-1749
Author(s):  
Alexandre A. Cavalcante
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Tensile Load ◽  
Specimen Geometry ◽  
Layer By Layer ◽  
Testing Specimen ◽  
Fused Deposition ◽  
Dog Bone ◽  
Anisotropic Mechanical Properties ◽  
Deposition Modeling

Abstract: Additive manufacturing (AM) by FDM (Fused Deposition Modeling) has been increasingly adopted due to the low cost of 3D printers as an option capable of producing parts with complex geometries. Since the FDM process is a layer-by-layer manufacturing method, the characterization of the behavior of parts manufactured by this technology, especially with regard to anisotropic mechanical properties, has led to many works relating printing parameters with tensile strength. However, the use of specimens with the conventional flat "dog bone" and cylindrical geometries specified in the ASTM-638 standards do not perfectly suit the special characteristics of parts produced by FDM, since these standards were created for solid and isotropic materials. A new geometry for specimens printed in FDM to study anisotropy transverse to layer deposition is suggested in this work. Problems such as slippage and crushing in the grips of the test machines due to the fragility of the bound between the beds, as well as the appearance of lateral forces that distort the results due to misalignment of the tensile load, twists and curvature of the specimens, normally observed in the Strain measurements by extensometers, are suppressed with the adoption of the new geometry presented in this work. Keywords: Fused Deposition Modeling, Additive Manufacturing, Mechanical Strength, Tensile Testing, Specimen Geometry

Carbon Nanotube Reinforced Fused Deposition Modeling Using Microwave Irradiation

2016 ◽  
Author(s):  
Meng Zhang ◽  
Xiaoxu Song ◽  
Weston Grove ◽  
Emmett Hull ◽  
Z. J. Pei ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Carbon Nanotube ◽  
Additive Manufacturing ◽  
Microwave Irradiation ◽  
Computer Aided Design ◽  
Fused Deposition Modeling ◽  
Layer By Layer ◽  
Sem Images ◽  
Fused Deposition ◽  
Deposition Modeling

Additive manufacturing (AM) is a class of manufacturing processes where material is deposited in a layer-by-layer fashion to fabricate a three-dimensional part directly from a computer-aided design model. With a current market share of 44%, thermoplastic-based additive manufacturing such as fused deposition modeling (FDM) is a prevailing technology. A key challenge for AM parts (especially for parts made by FDM) in engineering applications is the weak inter-layer adhesion. The lack of bonding between filaments usually results in delamination and mechanical failure. To address this challenge, this study embedded carbon nanotubes into acrylonitrile butadiene styrene (ABS) thermoplastics via a filament extrusion process. The vigorous response of carbon nanotubes to microwave irradiation, leading to the release of a large amount of heat, is used to melt the ABS thermoplastic matrix adjacent to carbon nanotubes within a very short time period. This treatment is found to enhance the inter-layer adhesion without bulk heating to deform the 3D printed parts. Tensile and flexural tests were performed to evaluation the effects of microwave irradiation on mechanical properties of the specimens made by FDM. Scanning electron microscopic (SEM) images were taken to characterize the fracture surfaces of tensile test specimens. The actual carbon nanotube contents in the filaments were measured by conducting thermogravimetric analysis (TGA). The effects of microwave irradiation on the electrical resistivity of the filament were also reported.

An Update on the Use of Alginate in Additive Biofabrication Techniques

2019 ◽  
Vol 25 (11) ◽  
pp. 1249-1264 ◽  
Author(s):  
Amoljit Singh Gill ◽  
Parneet Kaur Deol ◽  
Indu Pal Kaur
Keyword(s):  
Fused Deposition Modeling ◽  
Low Cost ◽  
Selective Laser Sintering ◽  
Layer By Layer ◽  
Three Dimension ◽  
Anionic Polymer ◽  
Fused Deposition ◽  
The Status ◽  
Deposition Modeling ◽  
Extrusion Printing

Background: Solid free forming (SFF) technique also called additive manufacturing process is immensely popular for biofabrication owing to its high accuracy, precision and reproducibility. Method: SFF techniques like stereolithography, selective laser sintering, fused deposition modeling, extrusion printing, and inkjet printing create three dimension (3D) structures by layer by layer processing of the material. To achieve desirable results, selection of the appropriate technique is an important aspect and it is based on the nature of biomaterial or bioink to be processed. Result & Conclusion: Alginate is a commonly employed bioink in biofabrication process, attributable to its nontoxic, biodegradable and biocompatible nature; low cost; and tendency to form hydrogel under mild conditions. Furthermore, control on its rheological properties like viscosity and shear thinning, makes this natural anionic polymer an appropriate candidate for many of the SFF techniques. It is endeavoured in the present review to highlight the status of alginate as bioink in various SFF techniques.

scholarly journals Energy and Eco-Impact Evaluation of Fused Deposition Modeling and Injection Molding of Polylactic Acid

2021 ◽  
Vol 13 (4) ◽  
pp. 1875
Author(s):  
Emmanuel Ugo Enemuoh ◽  
Venkata Gireesh Menta ◽  
Abdulaziz Abutunis ◽  
Sean O’Brien ◽  
Labiba Imtiaz Kaya ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Injection Molding ◽  
Polylactic Acid ◽  
Fused Deposition Modeling ◽  
Plastic Injection Molding ◽  
Measurement Models ◽  
Fused Deposition ◽  
Dog Bone ◽  
Deposition Modeling ◽  
Plastic Injection

There is limited knowledge about energy and carbon emission performance comparison between additive fused deposition modeling (FDM) and consolidation plastic injection molding (PIM) forming techniques, despite their recent high industrial applications such as tools and fixtures. In this study, developed empirical models focus on the production phase of the polylactic acid (PLA) thermoplastic polyester life cycle while using FDM and PIM processes to produce American Society for Testing and Materials (ASTM) D638 Type IV dog bone samples to compare their energy consumption and eco-impact. It was established that energy consumption by the FDM layer creation phase dominated the filament extrusion and PLA pellet production phases, with, overwhelmingly, 99% of the total energy consumption in the three production phases combined. During FDM PLA production, about 95.5% of energy consumption was seen during actual FDM part building. This means that the FDM process parameters such as infill percentage, layer thickness, and printing speed can be optimized to significantly improve the energy consumption of the FDM process. Furthermore, plastic injection molding consumed about 38.2% less energy and produced less carbon emissions per one kilogram of PLA formed parts compared to the FDM process. The developed functional unit measurement models can be employed in setting sustainable manufacturing goals for PLA production.

scholarly journals Automated Testing and Characterization of Additive Manufacturing (ATCAM)

2021 ◽  
Author(s):  
Arash Alex Mazhari ◽  
Randall Ticknor ◽  
Sean Swei ◽  
Stanley Krzesniak ◽  
Mircea Teodorescu
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Cell System ◽  
Automated Testing ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Machine Calibration

AbstractThe sensitivity of additive manufacturing (AM) to the variability of feedstock quality, machine calibration, and accuracy drives the need for frequent characterization of fabricated objects for a robust material process. The constant testing is fiscally and logistically intensive, often requiring coupons that are manufactured and tested in independent facilities. As a step toward integrating testing and characterization into the AM process while reducing cost, we propose the automated testing and characterization of AM (ATCAM). ATCAM is configured for fused deposition modeling (FDM) and introduces the concept of dynamic coupons to generate large quantities of basic AM samples. An in situ actuator is printed on the build surface to deploy coupons through impact, which is sensed by a load cell system utilizing machine learning (ML) to correlate AM data. We test ATCAM’s ability to distinguish the quality of three PLA feedstock at differing price points by generating and comparing 3000 dynamic coupons in 10 repetitions of 100 coupon cycles per material. ATCAM correlated the quality of each feedstock and visualized fatigue of in situ actuators over each testing cycle. Three ML algorithms were then compared, with Gradient Boost regression demonstrating a 71% correlation of dynamic coupons to their parent feedstock and provided confidence for the quality of AM data ATCAM generates.

Knowledge-Based Design of Artificial Neural Network Topology for Additive Manufacturing Process Modeling: A New Approach and Case Study for Fused Deposition Modeling

2018 ◽  
Vol 141 (2) ◽  
Author(s):  
Hari P. N. Nagarajan ◽  
Hossein Mokhtarian ◽  
Hesam Jafarian ◽  
Saoussen Dimassi ◽  
Shahriar Bakrani-Balani ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Expert Knowledge ◽  
Fused Deposition ◽  
Knowledge Based ◽  
Deposition Modeling ◽  
Artificial Neural

Additive manufacturing (AM) continues to rise in popularity due to its various advantages over traditional manufacturing processes. AM interests industry, but achieving repeatable production quality remains problematic for many AM technologies. Thus, modeling different process variables in AM using machine learning can be highly beneficial in creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers to make informed decisions about their products and processes. However, it is challenging to define an appropriate ANN topology that captures the AM system behavior. Toward that goal, an approach combining dimensional analysis conceptual modeling (DACM) and classical ANNs is proposed to create a new type of knowledge-based ANN (KB-ANN). This approach integrates existing literature and expert knowledge of the AM process to define a topology for the KB-ANN model. The proposed KB-ANN is a hybrid learning network that encompasses topological zones derived from knowledge of the process and other zones where missing knowledge is modeled using classical ANNs. The usefulness of the method is demonstrated using a case study to model wall thickness, part height, and total part mass in a fused deposition modeling (FDM) process. The KB-ANN-based model for FDM has the same performance with better generalization capabilities using fewer weights trained, when compared to a classical ANN.

The influence of load direction, microstructure, raster orientation on the quasi-static response of fused deposition modeling ABS

2019 ◽  
Vol 25 (3) ◽  
pp. 462-472 ◽  
Author(s):  
Oluwakayode Bamiduro ◽  
Gbadebo Owolabi ◽  
Mulugeta A. Haile ◽  
Jaret C. Riddick
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Mechanical Response ◽  
Mechanical Performance ◽  
Bead Geometry ◽  
Static Response ◽  
Load Direction ◽  
Content Type ◽  
Fused Deposition ◽  
Deposition Modeling

Purpose The continual growth of additive manufacturing has increased tremendously because of its versatility, flexibility and high customization of geometric structures. However, design hurdles are presented in understanding the relationship between the fabrication process and materials microstructure as it relates to the mechanical performance. The purpose of this paper is to investigate the role of build architecture and microstructure and the effects of load direction on the static response and mechanical properties of acrylonitrile butadiene styrene (ABS) specimens obtained via the fused deposition modeling (FDM) processing technique. Design/methodology/approach Among additive manufacturing processes, FDM is a prolific technology for manufacturing ABS. The blend of ABS combines strength, rigidity and toughness, all of which are desirable for the production of structural materials in rapid manufacturing applications. However, reported literature has varied widely on the mechanical performance due to the proprietary nature of the ABS material ratio, ultimately creating a design hurdle. While prior experimental studies have studied the mechanical response via uniaxial tension testing, this study has aimed to understand the mechanical response of ABS from the materials’ microstructural point of view. First, ABS specimen was fabricated via FDM using a defined build architecture. Next, the specimens were mechanically tested until failure. Then finally, the failure structures were microstructurally investigated. In this paper, the effects of microstructural evolution on the static mechanical response of various build architecture of ABS aimed at FDM manufacturing technique was analyzed. Findings The results show that the rastering orientation of 0/90 exhibited the highest tensile strength followed by fracture at its maximum load. However, the “45” bead direction of the ABS fibers displayed a cold-drawing behavior before rupture. The morphology analyses before and after tensile failure were characterized by a scanning electron microscopy (SEM) which highlighted the effects of bead geometry (layers) and areas of stress concentration such as interstitial voids in the material during build, ultimately compromising the structural integrity of the specimens. Research limitations/implications The ability to control the constituents and microstructure of a material during fabrication is significant to improving and predicting the mechanical performance of structural additive manufacturing components. In this report, the effects of microstructure on the mechanical performance of FDM-fabricated ABS materials was discussed. Further investigations are planned in understanding the effects of ambient environmental conditions (such as moisture) on the ABS material pre- and post-fabrication. Originality/value The study provides valuable experimental data for the purpose of understanding the inter-dependency between build parameters and microstructure as it relates to the specimens exemplified strength. The results highlighted in this study are fundamental to the development of optimal design of strength and complex ultra-lightweight structure efficiency.

Part Monitoring and Quality Assessment of Conformal Additive Manufacturing Using Image Reconstruction

2018 ◽  
Author(s):  
Michael D. Kutzer ◽  
Levi D. DeVries ◽  
Cooper D. Blas
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Digital Camera ◽  
Image Data ◽  
Digital Cameras ◽  
Public And Private ◽  
The Public ◽  
Fused Deposition ◽  
Complex Part ◽  
Deposition Modeling

Additive manufacturing (AM) technologies have become almost universal in concept development, prototyping, and education. Advances in materials and methods continue to extend this technology to small batch and complex part manufacturing for the public and private sectors. Despite the growing popularity of digital cameras in AM systems, use of image data for part monitoring is largely unexplored. This paper presents a new method for estimating the 3D internal structure of fused deposition modeling (FDM) processes using image data from a single digital camera. Relative transformations are established using motion capture, and the 3D model is created using knowledge of the deposition path coupled with assumptions about the deposition cross-section. Results show that part geometry can be estimated and visualized using the methods presented in this work.

scholarly journals EFFECT OF EXTRUSION PROCESS PARAMETERS ON MECHANICAL PROPERTIES OF 3D PRINTED PLA PRODUCT

2021 ◽  
Vol 6 (2) ◽  
pp. 119
Author(s):  
Nanang Ali Sutisna ◽  
Rakha Amrillah Fattah
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Extrusion Process ◽  
Experimental Procedure ◽  
Fused Deposition ◽  
Novel Approach ◽  
Deposition Modeling ◽  
3D Printed ◽  
3D Digital Models

The method of producing items through synchronously depositing material level by level, based on 3D digital models, is named Additive Manufacturing (AM) or 3D-printing. Amongs many AM methods, the Fused Deposition Modeling (FDM) technique along with PLA (Polylactic acid) material is commonly used in additive manufacturing. Until now, the mechanical properties of the AM components could not be calculated or estimated until they've been assembled and checked. In this work, a novel approach is suggested as to how the extrusion process affects the mechanical properties of the printed component to obtain how the parts can be manufactured or printed to achieve improved mechanical properties. This methodology is based on an experimental procedure in which the combination of parameters to achieve an optimal from a manufacturing experiment and its value can be determined, the results obtained show the effect of the extrusion process affects the mechanical properties.

scholarly journals Desain dan Pembuatan Prototype Piston Honda MEGAPRO FI Menggunakan 3D Printing

2020 ◽  
Vol 1 (2) ◽  
pp. 81-91
Author(s):  
Frince Marbun ◽  
Richard A.M. Napitupulu
Keyword(s):  
3D Printing ◽  
Computer Aided Design ◽  
Fused Deposition Modeling ◽  
Layer By Layer ◽  
Printing Technology ◽  
3D Printing Technology ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Manufacturing Technologies ◽  
Aided Design

3D printing technology has great potential in today's manufacturing world, one of its uses is in making miniatures or prototypes of a product such as a piston. One of the most famous and inexpensive 3D printing (additive manufacturing) technologies is Fused Deposition Modeling (FDM), the principle FDM works by thermoplastic extrusion through a hot nozzle at melting temperature then the product is made layer by layer. The two most commonly used materials are ABS and PLA so it is very important to know the accuracy of product dimensions. FDM 3D Printing Technology is able to make duplicate products accurately using PLA material. FDM machines work by printing parts that have been designed by computer-aided design (CAD) and then exported in the form of STL or .stl files and uploaded to the slicer program to govern the printing press according to the design. Using Anet A8 brand 3D printing tools that are available to the public, Slicing of general CAD geometry files such as autocad and solidwork is the basis for making this object. This software is very important to facilitate the design process to be printed. Some examples of software that can be downloaded and used free of charge such as Repetier-Host and Cura. by changing the parameters in the slicer software is very influential in the 3D printing manufacturing process.

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