Additive Manufacturing - A Literature Review

2020 ◽  
Vol 979 ◽  
pp. 74-83
Author(s):  
Penumuru Kumar ◽  
Arumugam Mahamani ◽  
B. Durga Prasad
Keyword(s):  
Additive Manufacturing ◽  
Literature Review ◽  
Polymer Composites ◽  
Fused Deposition Modeling ◽  
Fused Deposition ◽  
Wide Range ◽  
Recent Developments ◽  
Deposition Modeling ◽  
Manufacturing Methods ◽  
Materials Used

In the present scenario, the industries are looking for creating the model quickly and making the prototype. Additive manufacturing (AM) is a rising technology for a hefty choice of applications. This route has plenty of advantages such as the availability of a wide range of materials, fabrication speed and resolution of the final components. The current paper deals with the review of the recent developments in additive manufacturing methods and their applications. Further, the discussion has been made about the various materials used for additive manufacturing such as ceramic, polymer, composites and biomaterials. The survey denotes that fused deposition modeling has received the widespread attention of the researchers. Finally, some of the gaps in the research are found and reported.

Special Issue on Additive Manufacturing with Metals

2019 ◽  
Vol 13 (3) ◽  
pp. 329-329
Author(s):  
Tatsuaki Furumoto
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Lead Times ◽  
Special Issue ◽  
Titanium Aluminum Alloys ◽  
Fused Deposition ◽  
Recent Developments ◽  
Deposition Modeling ◽  
Directed Energy ◽  
The Many

Additive manufacturing (AM) with metals is currently one of the most promising techniques for 3D-printed structures, as it has tremendous potential to produce complex, lightweight, and functionally-optimized parts. The medical, aerospace, and automotive industries are some of the many expected to reap particular benefits from the ability to produce high-quality models with reduced manufacturing costs and lead times. The main advantages of AM with metals are the flexibility of the process and the wide variety of metal materials that are available. Various materials, including steel, titanium, aluminum alloys, and nickel-based alloys, can be employed to produce end products. The objective of this special issue is to collect recent research works focusing on AM with metals. This issue includes 5 papers covering the following topics: ===danraku===- Powder bed fusion (PBF) ===danraku===- Directed energy deposition (DED) ===danraku===- Wire and arc-based AM (WAAM) ===danraku===- Binder jetting (BJT) ===danraku===- Fused deposition modeling (FDM) This issue is expected to help readers understand recent developments in AM, leading to further research. We deeply appreciate the contributions of all authors and thank the reviewers for their incisive efforts.

scholarly journals Impact of Temperature and Material Variation on Mechanical Properties of Parts Fabricated with Fused Deposition Modelling (FDM) Additive Manufacturing

2021 ◽  
Author(s):  
M. Hossein Sehhat ◽  
Ali Mahdianikhotbesara ◽  
Farzad Yadegari
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Acrylonitrile Butadiene Styrene ◽  
Tensile Tests ◽  
Fused Deposition Modelling ◽  
Fused Deposition ◽  
Operational Temperature ◽  
Deposition Modeling ◽  
Materials Used

Abstract Additive Manufacturing (AM) can be deployed for space exploration purposes, such as fabricating different components of robots’ bodies. The produced AM parts should have desirable thermal and mechanical properties to withstand the extreme environmental conditions, including the severe temperature variations on moon or other planets which cause changes in parts’ strengths and may fail their operation. Therefore, the correlation between operational temperature and mechanical properties of AM fabricated parts should be evaluated. In this study, three different types of polymers, including polylactic acid (PLA), polyethylene terephthalate glycol (PETG), and acrylonitrile butadiene styrene (ABS), were used in Fused Deposition Modeling (FDM) process to fabricate several parts. The mechanical properties of produced parts were then investigated at various temperatures to generate knowledge on the correlation between temperature and type of material. When varying the operational temperature during tensile tests, the material’s glass transition temperature was found influential in determining the type of material failure. Among the materials used, ABS showed the best mechanical properties at all temperatures due to its highest glass transmission temperatures. The results of statistical analysis indicated the temperature as the significant factor on tensile strength while the change in material did not show a significant effect.

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.

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.

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.

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