scholarly journals Comparative Screening of the Structural and Thermomechanical Properties of FDM Filaments Comprising Thermoplastics Loaded with Cellulose, Carbon and Glass Fibers

Materials ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 422 ◽  
Author(s):  
Alp Karakoç ◽  
Vibhore K. Rastogi ◽  
Tapani Isoaho ◽  
Blaise Tardy ◽  
Jouni Paltakari ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Glass Fibers ◽  
Thermal Analyses ◽  
Polymeric Materials ◽  
Material Strength ◽  
Fused Deposition ◽  
Dog Bone ◽  
Infrared Measurements ◽  
Microstructural Effects

Additive manufacturing (AM) has been rapidly growing for a decade in both consumer and industrial products. Fused deposition modeling (FDM), one of the most widely used additive manufacturing methods, owes its popularity to cost effectiveness in material and equipment investment. Current efforts are aimed toward high load-bearing capacity at low material costs. However, the mechanical reliability of end-products derived from these compositions and their dependence on microstructural effects, have remained as major limitations. This is mainly owing to the unknown mechanics of the materials, including the reinforcing or filler components and their interphase/interface compatibility. For this reason, here we investigate the most relevant commercial polymeric materials used in composite filaments, associated phases and the characterization protocols that can guide component selection, screening and troubleshooting. We first present thermal analyses (thermogravimetric, TGA and differential scanning calorimetry, DSC) in relation to the constituent fractions and identify the type of polymer for uses in filaments production. The influence of various fillers is unveiled in terms of the crystallization behavior of derived 3D-printed parts. To understand the microstructural effects on the material strength, we carry out a series of tensile experiments on 3-D printed dog-bone shaped specimens following ISO standards. Simultaneously, real-time thermal energy dissipation and damage analyses are applied by using infrared measurements at fast frame rates (200 Hz) and high thermal resolution (50 mK). The failure regions of each specimen are examined via optical, scanning and transmission electron microscopies. The results are used to reveal new insights into the size, morphology and distribution of the constituents and interphases of polymer filaments for FDM. The present study represents advancement in the field of composite filament fabrication, with potential impact in the market of additive manufacturing.

Additive manufacturing of shape memory polymers: effects of print orientation and infill percentage on shape memory recovery properties

2020 ◽  
Vol 26 (9) ◽  
pp. 1593-1602
Author(s):  
Jorge Villacres ◽  
David Nobes ◽  
Cagri Ayranci
Keyword(s):  
Additive Manufacturing ◽  
Shape Memory ◽  
Shape Recovery ◽  
Fused Deposition Modeling ◽  
Large Strain ◽  
Shape Memory Polymers ◽  
Polymeric Materials ◽  
Content Type ◽  
Fused Deposition ◽  
Memory Recovery

Purpose The purpose of this paper is to study the shape memory properties of SMP samples produced through a MEAM process. Fused deposition modeling or, as it will be referred to in this paper, material extrusion additive manufacturing (MEAM) is a technique in which polymeric materials are extruded though a nozzle creating parts via accumulation and joining of different layers. These layers are fused together to build three-dimensional objects. Shape memory polymers (SMP) are stimulus responsive materials, which have the ability to recover their pre-programmed form after being exposed to a large strain. To induce its shape memory recovery movement, an external stimulus such as heat needs to be applied. Design/methodology/approach This project investigates and characterizes the influence of print orientation and infill percentage on shape recovery properties. The analyzed shape recovery properties are shape recovery force, shape recovery speed and time elapsed before activation. To determine whether the analyzed factors produce a significant variation on shape recovery properties, t-tests were performed with a 95% confidence factor between each analyzed level. Findings Results proved that print angle and infill percentage do have a significant impact on recovery properties of the manufactured specimens. Originality/value The manufacturing of SMP objects through a MEAM process has a vast potential for different applications; however, the shape recovery properties of these objects need to be analyzed before any practical use can be developed. These have not been studied as a function of print parameters, which is the focus of this study.

scholarly journals Dynamical Mechanical and Thermal Analyses of Biodegradable Raw Materials for Additive Manufacturing

Materials ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1819 ◽  
Author(s):  
Simona-Nicoleta Mazurchevici ◽  
Andrei-Danut Mazurchevici ◽  
Dumitru Nedelcu
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Raw Materials ◽  
Thermal Analyses ◽  
Xrd Analysis ◽  
Mechanical Analysis ◽  
Elastic Behavior ◽  
Scanning Calorimetry ◽  
Calorimetric Analysis ◽  
Fused Deposition

In order to find new ways to ensure sustainable development on a global level, it is essential to combine current top technologies, such as additive manufacturing, with the economic, ecological, and social fields. One objective of this paper refers to wire manufacture such as Arboblend V2 Nature, Arbofill Fichte, and Arboblend V2 Nature reinforced with Extrudr BDP “Pearl” (BDP—Biodegradable Plastic) in order to replace the plastic materials. After wire manufacture by extrusion, the diameter accuracy was analyzed compared with the Fiber Wood wire using SEM analyses and also EDAX—Energy Dispersive X-ray Analysis and DSC—Differential Scanning Calorimetry analyses were done in order to identify their elemental composition and the phase transitions suffered by the materials during heating. Using the samples obtained through the Fused Deposition Modeling (FDM) method, both crystalline phases and chemical composition information (XRD analysis) were identified, as well was determined the visco-elastic behavior Dynamic Mechanical Analysis (DMA), for the reinforced material and Fiber Wood. The extruded wires have allowed size for the printing equipment, around 1.75 mm with tolerance of ± 0.05 mm. The wire material diagrams, Arboblend V2 Nature reinforced with Extrudr BDP “Pearl” and Fiber Wood following the calorimetric analysis, presented peaks corresponding to material crystallization, while Arbofill Fichte revealed only the melting temperature. The storage module was almost double in case of Arboblend V2 Nature reinforced with Extrudr BDP “Pearl” compared with Fiber Wood and materials’ melting temperatures were confirmed by the analyses carried out.

Development of Porous Polymer-Ceramic Composites as Bone Grafts

2002 ◽  
Vol 726 ◽  
Author(s):  
Samar Kalita ◽  
John Finley ◽  
Susmita Bose ◽  
Howard Hosick ◽  
Amit Bandyopadhyay
Keyword(s):  
Pore Size ◽  
Fused Deposition Modeling ◽  
Average Pore Size ◽  
Polymeric Materials ◽  
Ceramic Composites ◽  
Porous Polymer ◽  
Fused Deposition ◽  
Dog Bone ◽  
Osteoblast Cell Line ◽  
Controlled Porosity

AbstractBiomaterials have made significant contributions to the advancement of modern health care and drug delivery industries. The present research is based on development of porous polymerceramic composite scaffolds using polypropylene (PP) polymer and tricalcium phosphate (TCP) ceramic for bone-graft applications. Three dimensionally interconnected controlled porosity scaffolds were fabricated using a fused deposition modeling (FDM) system. First, ceramic and polymeric materials were compounded under high shear using a torque rheometer. Compounded materials were then extruded to a 1.78mm diameter continuous filament using a single screw extruder. These filaments were used as a feedstock material for an FDM 1650 machine for direct fabrication of controlled porosity parts. Hg-porosimetry was done to determine pore size and their distribution in these structures. Tensile properties of neat composites and as received polymer were measured and compared using standard dog bone samples. Uniaxial compression tests were performed on cylindrical porous samples having average pore size of 160 μm and 36 vol% porosity. These samples showed an average ultimate compressive strength of 12.7 MPa. Average compressive modulus was calculated as 263 MPa. Cytotoxicity and cell proliferation studies were conducted with OPC1 modified human osteoblast cell-line. It was found that composite matrices were non-toxic and they showed excellent cell growth with OPC1 cells.

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

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 On the Post-Processing of 3D-Printed ABS Parts

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1559
Author(s):  
Mohammad Reza Khosravani ◽  
Jonas Schüürmann ◽  
Filippo Berto ◽  
Tamara Reinicke
Keyword(s):  
Surface Treatment ◽  
Fused Deposition Modeling ◽  
Three Dimensional ◽  
Acrylonitrile Butadiene Styrene ◽  
Experimental Tests ◽  
Fracture Load ◽  
Post Processing ◽  
Fused Deposition ◽  
Dog Bone ◽  
3D Printed

Application of Additive Manufacturing (AM) has significantly increased in the past few years. AM also known as three-dimensional (3D) printing has been currently used in fabrication of prototypes and end-use products. Considering the new applications of additively manufactured components, it is necessary to study structural details of these parts. In the current study, influence of a post-processing on the mechanical properties of 3D-printed parts has been investigated. To this aim, Acrylonitrile Butadiene Styrene (ABS) material was used to produce test coupons based on the Fused Deposition Modeling (FDM) process. More in deep, a device was designed and fabricated to fix imperfection and provide smooth surfaces on the 3D-printed ABS specimens. Later, original and treated specimens were subjected to a series of tensile loads, three-point bending tests, and water absorption tests. The experimental tests indicated fracture load in untreated dog-bone shaped specimen was 2026.1 N which was decreased to 1951.7 N after surface treatment. Moreover, the performed surface treatment was lead and decrease in tensile strength from 29.37 MPa to 26.25 MPa. Comparison of the results confirmed effects of the surface modification on the fracture toughness of the examined semi-circular bending components. Moreover, a 3D laser microscope was used for visual investigation of the specimens. The documented results are beneficial for next designs and optimization of finishing processes.

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.

Design, Development and Characterization of Linear, Soft Actuators via Additive Manufacturing

2018 ◽  
Author(s):  
Alfonso Costas ◽  
Daniel E. Davis ◽  
Yixian Niu ◽  
Sadegh Dabiri ◽  
Jose Garcia ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Fused Deposition Modeling ◽  
Single Step ◽  
Design Development ◽  
Initial Attempt ◽  
Fused Deposition ◽  
Piston Cylinder ◽  
Compact Size ◽  
Soft Actuators

Additive manufacturing has emerged as an alternative to traditional manufacturing technologies. In particular, industries like fluid power, aviation and robotics have the potential to benefit greatly from this technology, due to the design flexibility, weight reduction and compact size that can be achieved. In this work, the design process and advantages of using 3D printing to make soft linear actuators were studied and highlighted. This work explored the limitations of current additive manufacturing tolerances to fabricate a typical piston-cylinder assembly, and how enclosed bellow actuators could be used to overcome high leakage and friction issues experienced with a piston-cylinder type actuator. To do that, different 3D printing technologies were studied and evaluated (stereolithorgraphy and fused deposition modeling) in the pursuit of high-fidelity, cost-effective 3D printing. The initial attempt consisted of printing the soft actuators directly using flexible materials in a stereolithography-type 3D printer. However, these actuators showed low durability and poor performance. The lack of a reliable resin resulted in the replacement of this material by EcoFlex® 00-30 silicone and the use of a 3D printed mold to cast the actuators. These molds included a 3-D printed dissolvable core inside the cast actuator in order to finish the manufacturing process in one single step. An experimental setup to evaluate the capabilities of these actuators was developed. Results are shown to assess the steady-state and the dynamic characteristics of these actuators. These tests resulted into the stroke-pressure and stroke-time responses for a specific load given different proportional valve inputs.

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.

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