Numerical simulation of temperature field and stress field in fused deposition modeling

Huadong Yang,Sen Zhang 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.7

Fused deposition modeling (FDM) is a rapid prototyping technology developed quickly in recent years. However, the precision of forming part is a key factor to limit the development of fused deposition modeling. This paper established numerical model of temperature filed and stress filed for the forming process of fused deposition modeling by finite element modeling method and “birth-death element” technique. From the analysis of temperature gradient cloud picture, the result indicates that the temperature distributions are uneven along both X and Y directions, but the temperature distribution is uniform along Z direction. From the analysis of stress field for forming parts, the result can be found that deformation is focused on the plane XOY and no obvious stress concentration is observed on the plane XOZ and YOZ. Based on the comparison of temperature fields for four different scanning filling paths (honeycomb, grid, wiggle, rectilinear), the results show that the smallest temperature gradient is found for honeycomb scanning filling path. Based on the comparison of stress fields for four different scanning filling paths, the results show that the most uniform stress distribution and the smallest deformation is honeycomb scanning filling path which can provide guiding significance for actual processing.

Representation of surface roughness in fused deposition modeling

Ahn, D.,Kweon, J.H.,Kwon, S.,Song, J.,Lee, S. Elsevier 2009 Journal of materials processing technology Vol. No.

Most rapid prototyping (RP) technologies apply a layered manufacturing (LM) process to efficiently fabricate 3D physical models. However, a critical drawback that reduces the surface quality of the RP parts occurs by utilizing LM. Hence, topics related to surface roughness have been a key issue in RP. In this paper, a new approach to model surface roughness in fused deposition modeling (FDM) is proposed. Based on actual surface roughness distributions of FDM parts, a theoretical model to express surface roughness distribution according to changes in surface angle is presented by considering the main factors that crucially affect surface quality. The proposed expression is verified by implementation and comparison with empirical data. Also, the effectiveness of the main factors is analyzed and discussed.

Research On Solutions To Slicing Errors In FDM 3D Printing Of Thin-walled Structures

QINGYUAN ZHANG,이병춘 한국인터넷방송통신학회 2024 International Journal of Internet, Broadcasting an Vol.16 No.1

The desktop-level 3D printing machines makes it easier for independent designers to produce collectible models. Desktop 3D printers that use FDM (Fused Deposition Modeling) technology usually use a minimum nozzle diameter of 0.4mm. When using FDM printers to make Gunpla models, Thin slice structures are prone to slicing errors, which lead to deformation of printed objects and reduction in structural strength. This paper aims to analyze the printing model that produces errors, control a single variable among the three variables of slice layer height, slice wall thickness and filament type for comparative testing, and find a way to avoid gaps. To provide assistance for using FDM printers to build models containing thin-walled structures.

Enhancing Interlayer Adhesion of Fused Deposition Modeling through Thermo-mechanical Methods

A. Andreu(알베르토),S. Kim(김상래),Y.-J. Yoon(윤용진) Korean Society for Precision Engineering 2021 한국정밀공학회 학술발표대회 논문집 Vol.2021 No.11월

Although notable advancements in FDM 3D printing have been achieved, weak mechanical properties remain a barrier to produce functional components. This limitation is a result of weak interlayer bonding inherent to the layer-by-layer fabrication since the lower layers rapidly cool below glass transition temperature before the next one is deposited. This work presents an inexpensive solution that targets the process of interlayer bond formation to increase the mechanical properties of FDM printed components and reduce anisotropy. This is done through the installation of a heated roller to slightly compress each layer homogeneously onto the previous one after it has been printed. In summary, tensile testing shows a maximum UTS, tensile modulus and strain increase of 38.8, 19.4, and 359.6% respectively. Furthermore, flexural analysis shows a maximum increase in UFS, flexural modulus and strain of 13.5, 20.76, and 11.9% respectively. Lastly, DSC analysis shows an increase in crystallinity of tested samples from 2.7 to 8.6%. Thermo-mechanical methods are proposed since pressure forces can be used to increase filament surface contact, and heat can be used to enable longer diffusion and neck growth.

3D Printed Parts with Honeycomb Internal Pattern by Fused Deposition Modelling; Experimental Characterization and Production Optimization

Mahmoud Moradi,Saleh Meiabadi,Alexander Kaplan 대한금속·재료학회 2019 METALS AND MATERIALS International Vol.25 No.5

In the present study additive manufacturing of Polylactic acid by fused deposition modeling were investigated based on statisticalanalysis. The honeycomb internal pattern was employed to build inside of specimens due to its remarkable capability toresist mechanical loads. Simplify 3D was utilized to slice the 3D model and to adjust fixed parameters. Layer thickness, infillpercentage, and extruder temperature were considered as controlled variables, while maximum failure load (N), elongationat break (mm), part weight (g), and build time (min) were selected as output responses and analysed by response surfacemethod. Analysis of variance results identified layer thickness as the major controlled variable for all responses. Interactionof infill percentage and extruder temperature had a significant influence on elongation at break and therefore, tough fractureof printed parts. The input parameters were optimized to materialize tow criteria; the first one was to rise maximum failureload and the second was to attain tough fracture and lessen build time and part weight at a time. Optimal solutions wereexamined by experimental fabrication to evaluate the efficiency of the optimization method. There was a good agreementbetween empirical results and response surface method predictions which confirmed the reliability of predictive models. The optimal setting to fulfill the first criterion could bring on a specimen with more than 1500 (N) maximum failure loadand less than 9 (g) weight.

Application of an RBF Neural Network for FDM Parts’ Surface Roughness Prediction for Enhancing Surface Quality

Ebrahim Vahabli,Sadegh Rahmati 한국정밀공학회 2016 International Journal of Precision Engineering and Vol.17 No.12

To improve the surface roughness of parts fabricated using fused deposition modeling, modeling of the surface roughness distribution is used before the fabrication process to enable more precise planning of the additive manufacturing process. In this paper, a new methodology based on radial basis function neural networks (RBFNNs) is proposed for estimation of the surface roughness based on experimental results. The effective variables of the RBFNN are optimized using the imperialist competitive algorithm (ICA). The RBFNN-ICA model outperforms considerably comparing to the RBFNN model. A specific test part capable of evaluating the surface roughness distribution for varied surface build angles is built. To demonstrate the advantage of the recommended model, a performance comparison of the most well-known analytical models is carried out. The results of the evaluation confirm the capability of more fitted responses in the proposed modeling. The RBFNN and RBFNN-ICA models have mean absolute percentage error of 7.11% and 3.64%, respectively, and mean squared error of 7.48 and 2.27, respectively. The robustness of the network is studied based on the RBFNN’s effective variables evaluation and sensitivity analysis assessment for the contribution of input parameters. Finally, the comprehensive validity assessments confirm improved results using the recommended modeling.

Accuracy and precision of measurements performed on three- dimensional printed pelvises when compared to computed tomography measurements

Loic Larguier,Adrien-Maxence Hespel,Nathalie Jamet,Elise Mercier,Daniel Jouan,Nicolas Jardel,Sylvain Larrat 대한수의학회 2019 Journal of Veterinary Science Vol.20 No.3

The preoperative contouring of plates decreases the duration of surgery and improves the quality of the reduction of pelvic fractures. Patient-tailored three-dimensionally printed pelvises might be an interesting tool for achieving that purpose. Currently, no study has evaluated the accuracy of measurements performed on three-dimensional printed models in comparison with computed tomography data for complex bones, such as the pelvis. Thisstudy examined whether the measurements obtained on pelvises printed using dual-material fused deposition modeling technology are not significantly different from those obtained on computed tomography images. The computed tomography images of the pelvic region from 10 dogs were used to produce three-dimensionally printed models with a dual-material fused deposition-modeling process. Four segments were measured on both three-dimensionally printed models and computed tomography images. The measurements were performedby three observers and repeated twice. Concordance correlation coefficients were used to assess the precision and accuracy of the measurements as well as evaluate the agreement between the methods. The accuracy of measurements between the methods was > 0.99 for all measurements. The precision was almost perfect for AE (0.996), substantial for BD and BC (0.963 and 0.958, respectively), and moderate for CD (0.912). These results indicate that, despite some minor variations, the measurements performed on printed models reproduced the computed tomography data reliably.

Planar reinforcement by sheet type stiffeners for fused deposition modeling

Tae-Hyun Kim,Eun-Ho Lee 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.10

This paper presents a planar reinforcement (PR) method for fused deposition modeling. In the proposed PR method, planar reinforcing parts, such as metal sheets or carbon fiber film (CFF), are placed inside the structures laminated by additive manufacturing. The tensile, bending stiffness, and vibration characteristics of the planar reinforced structures were evaluated using mechanical tests (tensile, bending, and impact hammer tests). The mechanical properties of the planar reinforced specimens were compared with those of other specimens built by polylactic acid (PLA) and short carbon fiber reinforcement thermoplastic (SFRTP) filaments. Results show that the planar reinforced structures have greater stiffness than the other specimens. The experimental results are analyzed using the mixture equation of composite materials, and the difference in reinforcement effect caused by metal and CFF sheets is discussed.

3D printing of multiple container models and their trajectory tests in calm water

Li, Yi,Yu, Hanqi,Smith, Damon,Khonsari, M.M.,Thiel, Ryan,Morrissey, George,Yu, Xiaochuan Techno-Press 2022 Ocean systems engineering Vol.12 No.2

More and more shipping containers are falling into the sea due to bad weather. Containers lost at sea negatively affect the shipping line, the trader and the consumer, and the environment. The question of locating and recovering dropped containers is a challenging engineering problem. Model-testing of small-scaled container models is proposed as an efficient way to investigate their falling trajectories to salvage them. In this study, we first build a standard 20-ft container model in SOLIDWORKS. Then, a three-dimensional (3D) geometric model in the STL (Standard Tessellation Language) format is exported to a Stratasys F170 Fused Deposition Modeling (FDM) printer. In total, six models were made of acrylonitrile styrene acrylate (ASA) and printed for the purpose of testing. They represent three different loading conditions with different densities and center of gravity (COG). Two samples for each condition were tested. The physical models were dropped into the towing tank of University of New Orleans (UNO). From the experimental tests, it is found that the impact of the initial position after sinking can cause a certain initial rolling velocity, which may have a great impact on the lateral displacement, and subsequently affect the final landing position. This series of model tests not only provide experimental data for the study of the trajectory of box-shape objects but also provide a valuable reference for maritime salvage operations and for the pipeline layout design.

FDM 방식 3D 프린터에 대한 딥러닝 기반 물성 추정

임주현(Joo Hyeon Im),김원곤(Wongon Kim),안성훈(Sung-Hoon Ahn),윤병동(Byeng Dong Youn) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11

Additive manufacturing (AM) is playing a major role in Industry 4.0. AM can simplify the fabrication of complex shapes while minimizing manufacturing time and cost. However, the poor surface quality and weak mechanical properties of the output hinder the broad application of AM. In this study, we propose a deep learning-based method for estimating the mechanical property in a fused deposition modeling-type 3D printer. Acceleration signals were acquired in the process of outputting a tensile specimen through construction of a test-bed. In addition, a tensile test was performed using the specimen to collect information on mechanical properties. After that, features were extracted from the divided signals to analyze the correlation with the mechanical properties. Finally, the quality of highly correlated property was estimated through deep neural network. We confirmed that deep learning-based method is good at estimating property through mean square error loss and root mean square error.