Material Flow Rate Estimation in Material Extrusion Additive Manufacturing

2021 ◽  
Vol 13 (1) ◽  
pp. 46-56
Author(s):  
G.P. Greeff
Keyword(s):  
Additive Manufacturing ◽  
Flow Rate ◽  
Material Flow ◽  
Fused Deposition Modeling ◽  
Volumetric Flow Rate ◽  
Cost Effective ◽  
Fused Filament Fabrication ◽  
Material Extrusion ◽  
Fused Deposition ◽  
G Code

The additive manufacturing of products promises exciting possibilities. Measurement methodologies, which measure an in-process dataset of these products and interpret the results, are essential. However, before developing such a level of quality assurance several in-process measurands must be realized. One of these is the material flow rate, or rate of adding material during the additive manufacturing process. Yet, measuring this rate directly in material extrusion additive manufacturing presents challenges. This work presents two indirect methods to estimate the volumetric flow rate at the liquefier exit in material extrusion, specifically in Fused Deposition Modeling or Fused Filament Fabrication. The methods are cost effective and may be applied in future sensor integration. The first method is an optical filament feed rate and width measurement and the second is based on the liquefier pressure. Both are used to indirectly estimate the volumetric flow rate. The work also includes a description of linking the G-code command to the final print result, which may be used to create a per extrusion command model of the part.

scholarly journals Implementation of Fused Filament Fabrication in Dentistry

2021 ◽  
Vol 11 (14) ◽  
pp. 6444
Author(s):  
Jörg Lüchtenborg ◽  
Felix Burkhardt ◽  
Julian Nold ◽  
Severin Rothlauf ◽  
Christian Wesemann ◽  
...  
Keyword(s):  
Fused Deposition Modeling ◽  
Present Report ◽  
Cost Effective ◽  
Great Promise ◽  
Temperature Sensitive ◽  
Fused Filament Fabrication ◽  
Digital Light Processing ◽  
Fused Deposition ◽  
Surgical Guides ◽  
Novel Approach

Additive manufacturing is becoming an increasingly important technique for the production of dental restorations and assistive devices. The most commonly used systems are based on vat polymerization, e.g., stereolithography (SLA) and digital light processing (DLP). In contrast, fused filament fabrication (FFF), also known under the brand name fused deposition modeling (FDM), is rarely applied in the dental field. This might be due to the reduced accuracy and resolution of FFF compared to vat polymerization. However, the use of FFF in the dental sector seems very promising for in-house production since it presents a cost-effective and straight forward method. The manufacturing of nearly ready-to-use parts with only minimal post-processing can be considered highly advantageous. Therefore, the objective was to implement FFF in a digital dental workflow. The present report demonstrates the production of surgical guides for implant insertion by FFF. Furthermore, a novel approach using a temperature-sensitive filament for bite registration plates holds great promise for a simplified workflow. In combination with a medical-grade filament, a multi-material impression tray was printed for optimized impression taking of edentulous patients. Compared to the conventional way, the printed thermoplastic material is pleasant to model and can allow clean and fast work on the patient.

Evaluation of the Effect of Infill Pattern on Mechanical Stregnth of Additively Manufactured Specimen

2017 ◽  
Vol 887 ◽  
pp. 128-132 ◽  
Author(s):  
Shaheryar Atta Khan ◽  
Bilal Ahmed Siddiqui ◽  
Muhammad Fahad ◽  
Maqsood Ahmed Khan
Keyword(s):  
Additive Manufacturing ◽  
Open Source ◽  
Fused Deposition Modeling ◽  
Fused Filament Fabrication ◽  
Fused Deposition ◽  
Additive Manufacturing Technology ◽  
Internal Structures ◽  
The World ◽  
Build Time ◽  
Deposition Modeling

Additive manufacturing has stepped down from the world of Sci-Fi into reality. Since its conception in the 1980s the technology has come a long way. May variants of the technology are now available to the consumer. With the advent of custom built (open source) Fused Deposition Modeling based printing technology Fused Filament Fabrication (FFF), FDM/FFF has become the most used Additive Manufacturing technology. The effects of the different infill patterns of FDM/FFF on the mechanical properties of a specimen made from ABS are studied in this paper. It is shown that due to changes in internal structures, the tensile strength of the specimen changes. The study also investigate the effect of infill pattern on the build time of the specimen. Extensive testing yielded the optimal infill pattern for FDM/FFF. An open source Arduino based RepRap printer was used for the preparation of specimen and showed promising results for rapid prototyping of custom built parts to bear high loads. The study can help with the increase in the use of additive manufacturing for the manufacturing of mechanically functioning parts such as prosthetics

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

2018 ◽  
Vol 24 (4) ◽  
pp. 744-751 ◽  
Author(s):  
Jorge Villacres ◽  
David Nobes ◽  
Cagri Ayranci
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Shape Memory ◽  
Fused Deposition Modeling ◽  
Shape Memory Polymer ◽  
Longitudinal Axis ◽  
Layer By Layer ◽  
Content Type ◽  
Material Extrusion ◽  
Fused Deposition

Purpose Material extrusion additive manufacturing, also known as fused deposition modeling, is a manufacturing technique in which objects are built by depositing molten materials layer-by-layer through a nozzle. The use and application of this technique has risen dramatically over the past decade. This paper aims to first, report on the production and characterization of a shape memory polymer material filament that was manufactured to print shape memory polymer objects using material extrusion additive manufacturing. Additionally, it aims to investigate and outline the effects of major printing parameters, such as print orientation and infill percentage, on the elastic and mechanical properties of printed shape memory polymer samples. Design/methodology/approach Infill percentage was tested at three levels, 50, 75 and 100 per cent, while print orientation was tested at four different angles with respect to the longitudinal axis of the specimens at 0°, 30°, 60° and 90°. The properties examined were elastic modulus, ultimate tensile strength and maximum strain. Findings Results showed that print angle and infill percentage do have a significant impact on the manufactured test samples. Originality/value Findings can significantly influence the tailored design and manufacturing of smart structures using shape memory polymer and material extrusion additive manufacturing.

scholarly journals Development of multifunctional nanocomposites with 3-D printing additive manufacturing and low graphene loading

2018 ◽  
Vol 32 (3) ◽  
pp. 383-408 ◽  
Author(s):  
Brennan E Yamamoto ◽  
A Zachary Trimble ◽  
Brenden Minei ◽  
Mehrdad N Ghasemi Nejhad
Keyword(s):  
Additive Manufacturing ◽  
Geometric Modeling ◽  
Fused Deposition Modeling ◽  
Graphene Nanosheets ◽  
Three Dimensional ◽  
Acrylonitrile Butadiene Styrene ◽  
Polybutylene Terephthalate ◽  
Fused Filament Fabrication ◽  
Fused Deposition ◽  
Multifunctional Nanocomposites

Fused filament fabrication (FFF) or fused deposition modeling is an additive manufacturing (AM) process commonly used for geometric modeling and rapid prototyping of parts called three-dimensional (3-D) printing. Commonly used thermoplastic materials in FFF 3-D printing AM are acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), and polybutylene terephthalate (PBT). However, these materials exhibit relatively low strength and toughness. Therefore, it is desirable to improve various properties of thermoplastics in 3-D printing AM by employing nanotechnology. The combination of 3-D printing and nanotechnology opens new venues for the manufacture of 3-D engineered materials with optimized properties and multifunctionality (e.g. mechanical, electrical, and thermal properties). Hence, in this work, the multifunctional property improvement effects of graphene oxide (GO) on thermoplastic materials suitable for 3-D printing AM are investigated. Low loading of GO with carboxyl and hydroxyl surface functional groups is incorporated into thermoplastic materials suitable for 3-D printing AM by a special mixing technique. ABS is chosen in this study due to its availability. Graphene nanosheets are employed to improve the properties of the developed nanocomposites by 3-D printing AM. GO is chosen to improve the dispersion of graphene nanosheets into the thermoplastic system to increase their interfacial adhesion. A multifunctional property improvement is observed in the developed nanocomposite with less than 0.1 wt% GO. Employing ASTM standard tests, it was found that at a very small loading of 0.06% by weight, GO could improve the properties of the thermoplastic in terms of strength, strain-to-failure, and toughness, while maintaining the stiffness, rendering the developed nanocomposites suitable for various applications of static and dynamic loading. GOs are now commercially available at low prices. At such low loadings, these graphene-type materials become economically feasible components of nanocomposites.

scholarly journals Effects of Rice Straw Powder (RSP) Size and Pretreatment on Properties of FDM 3D-Printed RSP/Poly(Lactic Acid) Biocomposites

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3234
Author(s):  
Wangwang Yu ◽  
Lili Dong ◽  
Wen Lei ◽  
Yuhan Zhou ◽  
Yongzhe Pu ◽  
...  
Keyword(s):  
Lactic Acid ◽  
Rice Straw ◽  
Fused Deposition Modeling ◽  
Flexural Modulus ◽  
Tensile Modulus ◽  
Cost Effective ◽  
Poly Lactic Acid ◽  
Fused Deposition ◽  
Interfacial Compatibility ◽  
3D Printed

To develop a new kind of environment-friendly composite filament for fused deposition modeling (FDM) 3D printing, rice straw powder (RSP)/poly(lactic acid) (PLA) biocomposites were FDM-3D-printed, and the effects of the particle size and pretreatment of RSP on the properties of RSP/PLA biocomposites were investigated. The results indicated that the 120-mesh RSP/PLA biocomposites (named 120#RSP/PLA) showed better performance than RSP/PLA biocomposites prepared with other RSP sizes. Infrared results showed that pretreatment of RSP by different methods was successful, and scanning electron microscopy indicated that composites prepared after pretreatment exhibited good interfacial compatibility due to a preferable binding force between fiber and matrix. When RSP was synergistically pretreated by alkaline and ultrasound, the composite exhibited a high tensile strength, tensile modulus, flexural strength, and flexural modulus of 58.59, 568.68, 90.32, and 3218.12 MPa, respectively, reflecting an increase of 31.19%, 16.48%, 18.75%, and 25.27%, respectively, compared with unmodified 120#RSP/PLA. Pretreatment of RSP also improved the thermal stability and hydrophobic properties, while reducing the water absorption of 120#RSP/PLA. This work is believed to provide highlights of the development of cost-effective biocomposite filaments and improvement of the properties of FDM parts.

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.

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.

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