Investigation of the Fused Deposition Modeling Additive Manufacturing I: Influence of Process Temperature on the Quality and Crystallinity of the Dosage Forms

2021 ◽  
Vol 22 (8) ◽  
Author(s):  
Jiaxiang Zhang ◽  
Rishi Thakkar ◽  
Vineet R. Kulkarni ◽  
Yu Zhang ◽  
Anqi Lu ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Dosage Forms ◽  
Process Temperature ◽  
Fused Deposition ◽  
Deposition Modeling

scholarly journals 3D Printing of Mini Tablets for Pediatric Use

2021 ◽  
Vol 14 (2) ◽  
pp. 143
Author(s):  
Julius Krause ◽  
Laura Müller ◽  
Dorota Sarwinska ◽  
Anne Seidlitz ◽  
Malgorzata Sznitowska ◽  
...  
Keyword(s):  
3D Printing ◽  
Fused Deposition Modeling ◽  
Dosage Forms ◽  
Small Scale ◽  
Fused Deposition ◽  
On Demand ◽  
Pediatric Diseases ◽  
Deposition Modeling ◽  
Manufacturing Techniques ◽  
Pediatric Use

In the treatment of pediatric diseases, suitable dosages and dosage forms are often not available for an adequate therapy. The use of innovative additive manufacturing techniques offers the possibility of producing pediatric dosage forms. In this study, the production of mini tablets using fused deposition modeling (FDM)-based 3D printing was investigated. Two pediatric drugs, caffeine and propranolol hydrochloride, were successfully processed into filaments using hyprolose and hypromellose as polymers. Subsequently, mini tablets with diameters between 1.5 and 4.0 mm were printed and characterized using optical and thermal analysis methods. By varying the number of mini tablets applied and by varying the diameter, we were able to achieve different release behaviors. This work highlights the potential value of FDM 3D printing for the on-demand production of patient individualized, small-scale batches of pediatric dosage forms.

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.

scholarly journals Utjecaj orijentacije na mehanička svojstva kod taložnog očvršćivanja

2020 ◽  
Vol 68 (4) ◽  
pp. 9-13
Author(s):  
Suzana Kutnjak-Mravlinčić ◽  
Ana Pilipović ◽  
Damir Godec
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Fused Deposition ◽  
Deposition Modeling

U industriji obuće, sve je veća pozornost na dizajnerski oblikovane potpetice. Ali taj dizajn uključuje mogućnost proizvodnje složene geometrije, personaliziranih potpetica male mase i ako je moguće jeftinu izradu. Tehnologija koja omogućuje i obuhvaća navedeno je aditivna proizvodnja (e. additive manufacturing - AM). Jedna od AM niskobudžetnih tehnologija i uređaja je postupak taloženog očvršćivanja (e. fused deposition modeling - FDM). U FDMu se proizvod izrađuje sloj po sloj, s različitim oblicima i gustoćom unutrašnjih ispuna što omogućuje izradu složenih geometrija i malu masu. Tijekom hodanja potpetica je opterećena odozgo pritisnom silom same težine osobe, dok je bočno izložena savijanju i udarnom opterećenju. Uzimajući u obzir dizajn same potpetice, potrebno je pravilno orijentirati proizvod u radnom prostoru stroja, jer orijentacija utječe na mehanička svojstva. U ovom su radu provedena ispitivanja savojnih svojstava kod dvije različite orijentacije s obzirom na proizvodnju stvarne potpetice i njene primjene. Nadalje, načinjena je analiza parametara prerade (debljina sloja, gustoća ispune i temperatura ispisa) kako bi se utvrdio njihov utjecaj na savojna svojstva u te dvije orijentacije.

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