A Study on Dimensional Accuracy of Fused Deposition Modeling (FDM) Processed Parts using Fuzzy Logic

2013 ◽  
Vol 13 (3) ◽  
pp. 183-197 ◽  
Author(s):  
Ranjeet Kumar Sahu ◽  
S.S. Mahapatra ◽  
Anoop Kumar Sood
Keyword(s):  
Experimental Data ◽  
Fuzzy Logic ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Experimental Results ◽  
Percentage Error ◽  
Fuzzy Decision Making ◽  
Fused Deposition ◽  
Deposition Modeling

AbstractFused Deposition Modeling (FDM) is an additive manufacturing technology for rapid prototyping that can build intricate parts in minimal time with least human intervention. The process parameters such as layer thickness, orientation, raster angle, raster width and air gap largely influence on dimensional accuracy of built parts which can be expressed as change in length, width and thickness. This paper presents experimental data and a fuzzy decision making logic in integration with the Taguchi method for improving the dimensional accuracy of FDM processed ABSP 400 parts. It is observed that length and width decreases but thickness shows positive deviation from desired value of the built part. Experimental results indicate that optimal factor settings for each response are different. Therefore, all the three responses are expressed in a single response index through fuzzy logic approach. The process parameters are optimized with consideration of all the performance characteristics simultaneously. Finally, an inference engine is developed to perform the inference operations on the rules for fuzzy prediction model based on Mamdani method. Experimental results are provided to confirm the effectiveness of the proposed approach. The predicted results are in good agreement with the values from the experimental data with average percentage error of less than 4.5.

scholarly journals Optimization of the Warpage of Fused Deposition Modeling Parts Using Finite Element Method

Polymers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3849
Author(s):  
Daniyar Syrlybayev ◽  
Beibit Zharylkassyn ◽  
Aidana Seisekulova ◽  
Asma Perveen ◽  
Didier Talamona
Keyword(s):  
Finite Element ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Experimental Studies ◽  
Experimental Results ◽  
Percentage Error ◽  
Internal Stresses ◽  
Fused Deposition ◽  
Taguchi Design Of Experiments ◽  
Deposition Modeling

Fused deposition modeling (FDM) is one of the most affordable and widespread additive manufacturing (AM) technologies. Despite its simplistic implementation, the physics behind this FDM process is very complex and involves rapid heating and cooling of the polymer feedstock. As a result, highly non-uniform internal stresses develop within the part, which can cause warpage deformation. The severity of the warpage is highly dependent on the process parameters involved, and therefore, currently extensive experimental studies are ongoing to assess their influence on the final accuracy of the part. In this study, a thermomechanical Finite Element model of the 3D printing process was developed using ANSYS. This model was compared against experimental results and several other analytical models available in the literature. The developed Finite Element Analysis (FEA) model demonstrated a good qualitative and quantitative correlation with the experimental results. An L9 orthogonal array, from Taguchi Design of Experiments, was used for the optimization of the warpage based on experimental results and numerical simulations. The optimum process parameters were identified for each objective and parts were printed using these process parameters. Both parts showed an approximately equal warpage value of 320 μm, which was the lowest among all 10 runs of the L9 array. Additionally, this model is extended to predict the warpage of FDM printed multi-material parts. The relative percentage error between the numerical and experimental warpage results for alternating and sandwich specimens are found to be 1.4% and 9.5%, respectively.

Parameters Optimization of FDM for the Quality of Prototypes Using an Integrated MCDM Approach

2019 ◽  
pp. 199-220
Author(s):  
Jagadish ◽  
Sumit Bhowmik
Keyword(s):  
Process Parameters ◽  
Shell Thickness ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Parameters Optimization ◽  
Layer Height ◽  
Fused Deposition ◽  
Optimal Setting ◽  
Deposition Modeling

Fused deposition modeling (FDM) is one of the emerging rapid prototyping (RP) processes in additive manufacturing. FDM fabricates the quality prototype directly from the CAD data and is dependent on the various process parameters, hence optimization is essential. In the present chapter, process parameters of FDM process are analyzed using an integrated MCDM approach. The integrated MCDM approach consists of modified fuzzy with ANP methods. Experimentation is performed considering three process parameters, namely layer height, shell thickness, and fill density, and corresponding response parameters, namely ultimate tensile strength, dimensional accuracy, and manufacturing time are determined. Thereafter, optimization of FDM process parameters is done using proposed method. The result shows that exp.no-4 yields the optimal process parameters for FDM and provides optimal parameters as layer height of 0.08 mm, shell thickness of 2.0 mm and fill density of 100%. Also, optimal setting provides higher ultimate TS, good DA, and lesser MT as well as improving the performance and efficiency of FDM.

Multifactor optimization of FDM process parameters for development of rapid tooling using SiC/Al2O3-reinforced LDPE filament

2018 ◽  
Vol 33 (5) ◽  
pp. 581-598 ◽  
Author(s):  
Piyush Bedi ◽  
Rupinder Singh ◽  
IPS Ahuja
Keyword(s):  
Particle Size ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Rapid Tooling ◽  
Scanning Calorimetry ◽  
Fused Deposition ◽  
Significant Process ◽  
Deposition Modeling ◽  
Sic Reinforcement

In this work, multifactor optimization of fused deposition modeling (FDM) process parameters has been reported for in-house prepared feedstock filament comprising of SiC/Al2O3 reinforced in recycled low-density polyethylene (LDPE) matrix with different particle sizes (i.e. single particle size (SPS), double particle size (DPS), and triple particle size (TPS) in different proportions). This study has been conducted on Al2O3-based DPS reinforcement in LDPE, which came out as a better solution during pilot experimentation in comparison to SPS, TPS, and SiC reinforcement, for printing of functional prototypes as rapid tooling (RT). The result of study suggests that infill angle in the FDM process is the most significant process parameter (contributing around 93%) for preparation of RT as regards dimensional accuracy and hardness is concerned. The RT so prepared is thermally stable as evident from differential scanning calorimetry analysis. Further, the photomicrographs observed in different planes suggest that, at the proposed settings, RT has a uniform distribution of reinforcement in LDPE matrix and can be gainfully used in light machining applications.

scholarly journals Analysis of the Influencing Factors of FDM-Supported Positions for the Compressive Strength of Printing Components

Materials ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4008
Author(s):  
Zhengkai Feng ◽  
Heng Wang ◽  
Chuanjiang Wang ◽  
Xiujuan Sun ◽  
Shuai Zhang
Keyword(s):  
Compressive Strength ◽  
Stress Intensity ◽  
Influencing Factors ◽  
Fused Deposition Modeling ◽  
Experimental Results ◽  
Compression Tests ◽  
Suspended State ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Reference Experiment

Fused deposition modeling (FDM) has the advantage of being able to process complex workpieces with relatively simple operations. However, when processing complex components in a suspended state, it is necessary to add support parts to be processed and formed, which indicates an excessive dependence on support. The stress intensity of the supported positions of the printing components can be modified by changing the supporting model of the parts, their density, and their distance in relation to the Z direction in the FDM printing settings. The focus of the present work was to study the influences of these three modified factors on the stress intensity of the supporting position of the printing components. In this study, 99 sets of compression tests were carried out using a position of an FDM-supported part, and the experimental results were observed and analyzed with a 3D topographic imager. A reference experiment on the anti-pressure abilities of the printing components without support was also conducted. The experimental results clarify how the above factors can affect the anti-pressure abilities of the supporting positions of the printing components. According to the results, when the supporting density is 30% and the supporting distance in the Z direction is Z = 0.14, the compressive strength of the printing component is lowest. When the supporting density of the printing component is ≤30% and the supporting distance in the Z direction is Z ≥ 0.10, the compressive strength of printing without support is greater than that of the linear support model. Under the same conditions, the grid-support method offers the highest compressive strength.

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