scholarly journals Degradation Classification of 3D Printing Thermoplastics Using Fourier Transform Infrared Spectroscopy and Artificial Neural Networks

2018 ◽  
Vol 8 (8) ◽  
pp. 1224 ◽  
Author(s):  
Sung-Uk Zhang
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
3D Printing ◽  
Thermal Degradation ◽  
Fused Deposition Modeling ◽  
Learning Strategy ◽  
Fused Deposition ◽  
3D Printed ◽  
Artificial Neural ◽  
And Control

Fused deposition modeling (FDM) is the most popular technology among 3D printing technologies because of inexpensive and flexible extrusion systems with thermoplastic materials. However, thermal degradation phenomena of the 3D-printed thermoplastics is an inevitable problem for long-term reliability. In the current study, thermal degradation of 3D-printed thermoplastics of ABS and PLA was studied. A classification methodology using deep learning strategy was developed so that thermal degradation of the thermoplastics could be classified using FTIR and Artificial Neural Networks (ANNs). Under given data and predefined rules for ANNs, ANN models with nine hidden layers showed the best results in terms of accuracy. To extend this methodology, other thermoplastics, several new datasets for ANNs, and control parameters of ANNs could be further investigated.

scholarly journals Classifying Degraded Three-Dimensionally Printed Polylactic Acid Specimens Using Artificial Neural Networks based on Fourier Transform Infrared Spectroscopy

2019 ◽  
Vol 9 (13) ◽  
pp. 2772
Author(s):  
Sung-Uk Zhang
Keyword(s):  
Neural Networks ◽  
Fourier Transform ◽  
Artificial Neural Networks ◽  
Thermal Degradation ◽  
Polylactic Acid ◽  
Fourier Transform Infrared ◽  
Ann Model ◽  
Flexible Material ◽  
3D Printed ◽  
Artificial Neural

Fused filament fabrication (FFF) is commonly employed in multiple domains to realize inexpensive and flexible material extrusion systems with thermoplastic materials. Among the several types of thermoplastic materials, polylactic acid (PLA), an environment-friendly bio-plastic, is commonly used for FFF for the sake of the safety of the manufacturing process. However, thermal degradation of three-dimensionally (3D)-printed PLA products is inevitable, and it is one of the failure mechanisms of thermoplastic products. The present study focuses on the thermal degradation of 3D-printed PLA specimens. A classification methodology using artificial neural networks (ANNs) based on Fourier transform infrared (FTIR) and was developed. Under the given experimental conditions, the ANN model could classify four levels of thermal degradation. Among the FTIR spectra recorded from 650 cm−1 to 4000 cm−1, the ANN model could suggest the best wavenumber ranges for classification.

Switchable Bistability in 3D Printed Shells With Bio-Inspired Architectures and Spatially Distributed Pre-Stress

2018 ◽  
Author(s):  
Karl Jin Ang ◽  
Katherine S. Riley ◽  
Jakob Faber ◽  
Andres F. Arrieta
Keyword(s):  
3D Printing ◽  
Room Temperature ◽  
Fused Deposition Modeling ◽  
Element Analysis ◽  
Fused Deposition ◽  
Spatially Distributed ◽  
Deposition Modeling ◽  
3D Printed ◽  
And Control ◽  
Careful Design

Using fused deposition modeling (FDM) 3D printing, we combine a bio-inspired bilayer architecture with distributed pre-stress and the shape memory behavior of polylactic acid (PLA) to manufacture shells with switchable bistability. These shells are stiff and monostable at room temperature, but become elastic and bistable with fast morphing when heated above their glass transition temperature. When cooled back down, the shells retain the configuration they were in at the elevated temperature and return to being stiff and monostable. These programmed deformations result from the careful design and control of how the filament is extruded by the printer and therefore, the resulting directional pre-stress. Parameter studies are presented on how to maximize the pre-stress for this application. The shells are analyzed using nonlinear finite element analysis. By leveraging the vast array of geometries accessible with 3D printing, this method can be extended to complex, multi-domain shells, including bio-inspired designs.

Biodegradable 3D Printed Polymer Microneedles for Transdermal Drug Delivery

2018 ◽  
Author(s):  
Michael A. Luzuriaga ◽  
Danielle R. Berry ◽  
John C. Reagan ◽  
Ronald A. Smaldone ◽  
Jeremiah J. Gassensmith
Keyword(s):  
Drug Delivery ◽  
3D Printing ◽  
Transdermal Drug Delivery ◽  
Fused Deposition Modeling ◽  
Fused Deposition ◽  
Modeling Software ◽  
Deposition Modeling ◽  
3D Printed ◽  
Microfabrication Technique ◽  
Mechanical Strengths

Biodegradable polymer microneedle (MN) arrays are an emerging class of transdermal drug delivery devices that promise a painless and sanitary alternative to syringes; however, prototyping bespoke needle architectures is expensive and requires production of new master templates. Here, we present a new microfabrication technique for MNs using fused deposition modeling (FDM) 3D printing using polylactic acid, an FDA approved, renewable, biodegradable, thermoplastic material. We show how this natural degradability can be exploited to overcome a key challenge of FDM 3D printing, in particular the low resolution of these printers. We improved the feature size of the printed parts significantly by developing a post fabrication chemical etching protocol, which allowed us to access tip sizes as small as 1 μm. With 3D modeling software, various MN shapes were designed and printed rapidly with custom needle density, length, and shape. Scanning electron microscopy confirmed that our method resulted in needle tip sizes in the range of 1 – 55 µm, which could successfully penetrate and break off into porcine skin. We have also shown that these MNs have comparable mechanical strengths to currently fabricated MNs and we further demonstrated how the swellability of PLA can be exploited to load small molecule drugs and how its degradability in skin can release those small molecules over time.

scholarly journals Mechanical Characterization and Thermodynamic Analysis of Laser-Polished Landscape Design Products Using 3D Printing

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2601
Author(s):  
Yue Ba ◽  
Yu Wen ◽  
Shibin Wu
Keyword(s):  
Surface Roughness ◽  
3D Printing ◽  
Fused Deposition Modeling ◽  
High Surface ◽  
Landscape Design ◽  
Laser Polishing ◽  
Fused Deposition ◽  
Design Structure ◽  
3D Printed ◽  
Stability And Accuracy

Recent innovations in 3D printing technologies and processes have influenced how landscape products are designed, built, and developed. In landscape architecture, reduced-size models are 3D-printed to replicate full-size structures. However, high surface roughness usually occurs on the surfaces of such 3D-printed components, which requires additional post-treatment. In this work, we develop a new type of landscape design structure based on the fused deposition modeling (FDM) technique and present a laser polishing method for FDM-fabricated polylactic acid (PLA) mechanical components, whereby the surface roughness of the laser-polished surfaces is reduced from over Ra 15 µm to less than 0.25 µm. The detailed results of thermodynamics and microstructure evolution are further analyzed during laser polishing. The stability and accuracy of the results are evaluated based on the standard deviation. Additionally, the superior tensile and flexural properties are examined in the laser-polished layer, in which the ultimate tensile strength (UTS) is increased by up to 46.6% and the flexural strength is increased by up to 74.5% compared with the as-fabricated components. Finally, a real polished landscape model is simulated and optimized using a series of scales.

scholarly journals 3D Printed Clamps for In Vitro Tensile Tests of Human Gracilis and the Superficial Third of Quadriceps Tendons

2021 ◽  
Vol 11 (6) ◽  
pp. 2563
Author(s):  
Ivan Grgić ◽  
Vjekoslav Wertheimer ◽  
Mirko Karakašić ◽  
Željko Ivandić
Keyword(s):  
3D Printing ◽  
Fused Deposition Modeling ◽  
Tensile Tests ◽  
Biomechanical Properties ◽  
Testing Procedure ◽  
Laboratory Equipment ◽  
Fused Deposition ◽  
Custom Made ◽  
3D Printed

Recent soft tissue studies have reported issues that occur during experimentation, such as the tissue slipping and rupturing during tensile loads, the lack of standard testing procedure and equipment, the necessity for existing laboratory equipment adaptation, etc. To overcome such issues and fulfil the need for the determination of the biomechanical properties of the human gracilis and the superficial third of the quadriceps tendons, 3D printed clamps with metric thread profile-based geometry were developed. The clamps’ geometry consists of a truncated pyramid pattern, which prevents the tendons from slipping and rupturing. The use of the thread application in the design of the clamp could be used in standard clamping development procedures, unlike in previously custom-made clamps. Fused deposition modeling (FDM) was used as a 3D printing technique, together with polylactic acid (PLA), which was used as a material for clamp printing. The design was confirmed and the experiments were conducted by using porcine and human tendons. The findings justify the usage of 3D printing technology for parts manufacturing in the case of tissue testing and establish independence from the existing machine clamp system, since it was possible to print clamps for each prepared specimen and thus reduce the time for experiment setup.

Artificial Neural Networks vs. Fuzzy Logic: Simple Tools to Predict and Control Complex Processes—Application to Plasma Spray Processes

2008 ◽  
Vol 17 (3) ◽  
pp. 365-376 ◽  
Author(s):  
Abdoul-Fatah Kanta ◽  
Ghislain Montavon ◽  
Michel Vardelle ◽  
Marie-Pierre Planche ◽  
Christopher C. Berndt ◽  
...  
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Artificial Neural Networks ◽  
Plasma Spray ◽  
Complex Processes ◽  
Artificial Neural ◽  
And Control ◽  
Control Complex

Einsatz von künstlichen neuronalen Netzwerken an Scannersystemen*/Application of artificial neural networks on scanner systems

2017 ◽  
Vol 107 (07-08) ◽  
pp. 536-540
Author(s):  
S. J. Pieczona ◽  
F. Muratore ◽  
M. F. Prof. Zäh
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural ◽  
And Control ◽  
Dynamic Enhancement

Zur Dynamiksteigerung von Scannersystemen werden verschiedene Arten von Modellierungs- und Regelungsmethoden in der Forschung genutzt. Jedoch sind Nichtlinearitäten, welche das Systemverhalten nachweisbar beeinflussen, in aller Regel nicht Teil der Untersuchung. Mit der Anwendung künstlicher neuronaler Netzwerke (KNN) wird das gesamte dynamische Systemverhalten sowohl für ein geregeltes als auch für ein ungeregeltes Scannersystem abgebildet. So wird geklärt, ob sich diese Art der Modellbildung für eine zukünftige Dynamiksteigerung eignet.   To enhance the dynamics of a scanner system, different methods of modelling and control are utilized. Nonlinearities, which have a certain impact on the system’s behavior, are generally ignored, though. By applying artificial neural networks, the overall dynamics of a controlled and an uncontrolled scanner could be represented. Thus, it will be clarified whether this kind of modelling is appropriate for a future dynamic enhancement.

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