Optimization of fused deposition modeling process parameters for dimensional accuracy using I-optimality criterion

Measurement ◽  
2016 ◽  
Vol 81 ◽  
pp. 174-196 ◽  
Author(s):  
Omar Ahmed Mohamed ◽  
Syed Hasan Masood ◽  
Jahar Lal Bhowmik
Keyword(s):  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Optimality Criterion ◽  
Dimensional Accuracy ◽  
Fused Deposition ◽  
Modeling Process ◽  
Deposition Modeling

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.

Evaluation of Fused Deposition Modeling Process Parameters Influence on 3D Printed Components by High Precision Metrology

2021 ◽  
pp. 281-295
Author(s):  
Alexandru D. Sterca ◽  
Roxana-Anamaria Calin ◽  
Lucian Cristian ◽  
Eva Maria Walcher ◽  
Osman Bodur ◽  
...  
Keyword(s):  
High Precision ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Fused Deposition ◽  
Modeling Process ◽  
Deposition Modeling ◽  
3D Printed ◽  
Precision Metrology

Dimensional Accuracy Evaluation of Rapid Prototyping Fused Deposition Modeling Process of FDM200mc Machine on Basic Engineering Profiles

2013 ◽  
Vol 465-466 ◽  
pp. 96-100 ◽  
Author(s):  
Zulkarnain Abdul Latiff ◽  
M.R.A. Rahman ◽  
F. Saad
Keyword(s):  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Accuracy Evaluation ◽  
Low Density ◽  
Varying Parameters ◽  
Fused Deposition ◽  
Modeling Process ◽  
Deposition Modeling ◽  
Optimum Type ◽  
Two Parameters

The purpose of this research is to study the accuracy of RP FDM Process. This research involves varying two parameters in building up the prototype which is the buildup angle and the sparse for each layer (volume of parts). The varying parameters were used in the FDM process for three types of specimen (profiles) which is the Cube, Cylinder and Pyramid. The varying parameters are the build up angle of 300, 650 and 900 and for the types of sparse, there are three types of sparse used which is Low Density (LD), High Density (HD) and Solid Type. The results of the dimensional accuracy are analyzed by calculating the percentage of difference of the dimensional measurement for the specimen and the actual dimension of it. The lesser difference, the better the dimensional accuracy. The conclusion of this study is the less complicated specimen shape for the FDM process, the more accurate of the dimensional accuracy with the optimum build up angle of 300 or less and the optimum type of sparse of Low Density Type (LD).

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.

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