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.

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.

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 Fused deposition modeling of polypropylene-aluminium silicate dihydrate microcomposites

e-Polymers ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 87-98
Author(s):  
Kilole Tesfaye Chaka
Keyword(s):  
Mechanical Properties ◽  
Fused Deposition Modeling ◽  
Tensile Modulus ◽  
Dimensional Accuracy ◽  
Processing Parameters ◽  
Screw Extruder ◽  
Scanning Calorimetry ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Aluminium Silicate

Abstract Polypropylene (PP) undergoes fast crystallization and resulting in rigorous shrinkage when it is subjected to high temperature likewise of the fused deposition modeling (FDM) process. This research study focuses on the investigation of the processing parameters and factors that decrease the warpage of PP during the FDM process. Aluminium silicate dihydrate (K) microparticles of different ratios were melt blended with PP by a twin-screw extruder, and filaments of about 1.7 mm diameter were extruded in a single screw extruder. Then, the extruded filaments were used to fabricate the dumbbells structure through the FDM process. The effects of optimizing the fused deposition temperature, coating the chamber with thick papers/fabrics, and coating a printer bed with PP material were also investigated in this study. Scanning and transmission electron microscopy, differential scanning calorimetry, melt flow, and mechanical properties testing instruments are used to analyze the microparticles dispersion, crystallization, flow, and mechanical properties of resulting samples. Uniformly dispersed filler and increased printing chamber temperature result in an increase of crystallization temperature and improve the dimensional accuracy of fused deposited specimens. The fused deposited PP-K10 wt% composite showed an improvement of up to 32% in tensile modulus compared to the neat PP.

Comparative Analysis of Different Methods of Rapid Tooling

2005 ◽  
Vol 475-479 ◽  
pp. 2873-2876
Author(s):  
Charles Martin ◽  
J.V. Sasutil ◽  
M. Kouhkan ◽  
E. Lorea ◽  
Rafiq Noorani
Keyword(s):  
Surface Roughness ◽  
Fused Deposition Modeling ◽  
Selective Laser Sintering ◽  
Dimensional Accuracy ◽  
Laser Sintering ◽  
Rapid Tooling ◽  
Composite Manufacturing ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Overall Performance

The purpose of this experiment was to compare different techniques that help improve conventional tooling. The methods investigated were chosen from both the methods of Rapid Tooling: direct and indirect. Six different methods were selected including, Sand Casting, Investment Casting, Fused Deposition Modeling (FDM), Direct Composite Manufacturing (DCM), Selective Laser Sintering (SLS), and Stereolithography (SLA). Several industrial corporations were contacted to help complete all six tests. Five parameters were selected for the comparison of these samples: dimensional accuracy, tensile strength, surface roughness, time for completion, and weight. Through comparison the strengths and weaknesses of each method was determined. It was found that different methods did better in various parameters. However, Selective Laser Sintering (SLS) seemed to have the best overall performance.

Development of three-dimensional printing filaments based on poly(lactic acid)/hydroxyapatite composites with potential for tissue engineering

2021 ◽  
pp. 002199832098856
Author(s):  
Marcela Piassi Bernardo ◽  
Bruna Cristina Rodrigues da Silva ◽  
Luiz Henrique Capparelli Mattoso
Keyword(s):  
Tissue Engineering ◽  
Lactic Acid ◽  
Fused Deposition Modeling ◽  
Three Dimensional ◽  
Poly Lactic Acid ◽  
Scanning Calorimetry ◽  
Three Dimensional Printing ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
3D Printed

Injured bone tissues can be healed with scaffolds, which could be manufactured using the fused deposition modeling (FDM) strategy. Poly(lactic acid) (PLA) is one of the most biocompatible polymers suitable for FDM, while hydroxyapatite (HA) could improve the bioactivity of scaffold due to its chemical composition. Therefore, the combination of PLA/HA can create composite filaments adequate for FDM and with high osteoconductive and osteointegration potentials. In this work, we proposed a different approache to improve the potential bioactivity of 3D printed scaffolds for bone tissue engineering by increasing the HA loading (20-30%) in the PLA composite filaments. Two routes were investigated regarding the use of solvents in the filament production. To assess the suitability of the FDM-3D printing process, and the influence of the HA content on the polymer matrix, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and scanning electron microscopy (SEM) were performed. The HA phase content of the composite filaments agreed with the initial composite proportions. The wettability of the 3D printed scaffolds was also increased. It was shown a greener route for obtaining composite filaments that generate scaffolds with properties similar to those obtained by the solvent casting, with high HA content and great potential to be used as a bone graft.

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