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.

scholarly journals PENENTUAN SETTING OPTIMAL MESIN 3D PRINTER BERBASIS FUSED DEPOSITION MODELING MENGGUNAKAN METODE TAGUCHI

2018 ◽  
Vol 4 (2) ◽  
Author(s):  
Anggit Prakasa ◽  
Setya Permana Sutisna ◽  
Anton Royanto Ahmad
Keyword(s):  
Experimental Design ◽  
Taguchi Method ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
High Accuracy ◽  
3D Printer ◽  
Fused Deposition ◽  
3D Printers ◽  
Optimal Setting ◽  
Deposition Modeling

<p>The 3D printers process is applied to create prototype components, but at the last 3D Printers are often applied as last products. So, high accuracy is required in this case. In this research will find the optimal<br />setting of the dimensional accuracy 3D printers based fused deposition modeling. The method used is<br />the Taguchi method, the reason for using this method its efficiency, this is because the Orthogonal<br />Array matrix requires less number of experiments than the classical experimental design. Analysis of<br />Variance is also needed in this method to see the factors that significantly influence the response<br />variable. The results of this study indicate that the factors that significantly influence is printspeed by<br />contributing 53.08%, flowrate contributes 16.4%, and temperature heater block contributes 3.85% and<br />optimal setting is temperature heater block 190º, print speed 60mm/s and flowrate 6.28 mm3/s. (A1,<br />C3 dan D2).</p>

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 Impact of Processing Parameters on the Quality of Pharmaceutical Solid Dosage Forms Produced by Fused Deposition Modeling (FDM)

Pharmaceutics ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 633 ◽  
Author(s):  
Muqdad Alhijjaj ◽  
Jehad Nasereddin ◽  
Peter Belton ◽  
Sheng Qi
Keyword(s):  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Quality Parameters ◽  
Dosage Forms ◽  
Proof Of Concept ◽  
Solid Dosage Forms ◽  
Solid Dosage ◽  
Fused Deposition ◽  
Deposition Modeling

Fused deposition modeling (FDM) three-dimensional (3D) printing is being increasingly explored as a direct manufacturing method to product pharmaceutical solid dosage forms. Despite its many advantages as a pharmaceutical formulation tool, it remains restricted to proof-of-concept formulations. The optimization of the printing process in order to achieve adequate precision and printing quality remains to be investigated. Demonstrating a thorough understanding of the process parameters of FDM and their impact on the quality of printed dosage forms is undoubtedly necessary should FDM advance from a proof-of-concept stage to an adapted pharmaceutical manufacturing tool. This article describes the findings of an investigation into a number of critical process parameters of FDM and their impact on quantifiable, pharmaceutically-relevant measures of quality. Polycaprolactone, one of the few polymers which is both suitable for FDM and is a GRAS (generally regarded as safe) material, was used to print internally-exposed grids, allowing examination of both their macroscopic and microstructural reproducibility of FDM. Of the measured quality parameters, dimensional authenticity of the grids was found to poorly match the target dimensions. Weights of the grids were found to significantly vary upon altering printing speed. Printing temperature showed little effect on weight. Weight uniformity per batch was found to lie within acceptable pharmaceutical quality limits. Furthermore, we report observing a microstructural distortion relating to printing temperature which we dub The First Layer Effect (FLE). Principal Component Analysis (PCA) was used to study factor interactions and revealed, among others, the existence of an interaction between weight/dosing accuracy and dimensional authenticity dictating a compromise between the two quality parameters. The Summed Standard Deviation (SSD) is proposed as a method to extract the optimum printing parameters given all the perceived quality parameters and the necessary compromises among them.

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.

The influence of support base on FDM accuracy in Z

2014 ◽  
Vol 20 (3) ◽  
pp. 182-191 ◽  
Author(s):  
Neri Volpato ◽  
José Aguiomar Foggiatto ◽  
Daniel Coradini Schwarz
Keyword(s):  
Fused Deposition Modeling ◽  
Surface Profile ◽  
Dimensional Accuracy ◽  
Contact Method ◽  
Content Type ◽  
Fused Deposition ◽  
Support Strategy ◽  
Deposition Modeling ◽  
Quality Surface

Purpose – The aim of this work is to study the influence of the quality (surface profile) of the support base on dimensional accuracy in the Z-axis in fused deposition modeling (FDM). Design/methodology/approach – The surface profile of a support base produced using a standard (default) FDM configuration is analyzed experimentally, and two new deposition configurations are proposed. Some parts are built using these approaches, and the influence of the profile on Z accuracy is investigated. The parts are examined using a contact method and measured using a caliper. Findings – The surface profile of the support base has a direct influence on FDM part accuracy in Z. The results show that the accuracy in the Z dimension of an FDM prototype can be increased by improving the surface quality of the support base. In cases where accuracy is paramount, this can be achieved by better planning (tuning) of the support strategy. Originality/value – A significant component of the Z error in FDM has been identified and studied.

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