Studies on Optimizing Process Parameters of Fused Deposition Modelling Technology for ABS

2017 ◽  
Vol 4 (10) ◽  
pp. 10994-11003 ◽  
Author(s):  
M. Vishwas ◽  
C.K. Basavaraj
2021 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Narongkorn Krajangsawasdi ◽  
Lourens G. Blok ◽  
Ian Hamerton ◽  
Marco L. Longana ◽  
Benjamin K. S. Woods ◽  
...  

Fused deposition modelling (FDM) is a widely used additive layer manufacturing process that deposits thermoplastic material layer-by-layer to produce complex geometries within a short time. Increasingly, fibres are being used to reinforce thermoplastic filaments to improve mechanical performance. This paper reviews the available literature on fibre reinforced FDM to investigate how the mechanical, physical, and thermal properties of 3D-printed fibre reinforced thermoplastic composite materials are affected by printing parameters (e.g., printing speed, temperature, building principle, etc.) and constitutive materials properties, i.e., polymeric matrices, reinforcements, and additional materials. In particular, the reinforcement fibres are categorized in this review considering the different available types (e.g., carbon, glass, aramid, and natural), and obtainable architectures divided accordingly to the fibre length (nano, short, and continuous). The review attempts to distil the optimum processing parameters that could be deduced from across different studies by presenting graphically the relationship between process parameters and properties. This publication benefits the material developer who is investigating the process parameters to optimize the printing parameters of novel materials or looking for a good constituent combination to produce composite FDM filaments, thus helping to reduce material wastage and experimental time.


Author(s):  
Varun Sharma ◽  
Khaja Moinuddin Shaik ◽  
Archita Choudhury ◽  
Pramod Kumar ◽  
Prateek Kala ◽  
...  

The present research paper attempts to study the effect of different process parameters on the dissolution rate during 3D printed tablets. Three-dimensional printing has the potential of serving tailored made tablets to cater personalized drug delivery systems. Fluorescein loaded PVA filaments through impregnation route was used to fabricate tablets based on Taguchi based design of experimentation using Fused Deposition Modelling (FDM). The effect of print speed, infill percentage and layer thickness were analyzed to study the effect on rate of dissolution. Infill percentage followed by print speed were found to be critical parameters affecting dissolution rate. The data analysis provided an insight into the study of interaction among different 3D printing parameters to develop an empirical relation for percentage release of the drug in human body.


2020 ◽  
Vol 27 ◽  
pp. 1794-1800
Author(s):  
R. Srinivasan ◽  
N. Aravindkumar ◽  
S. Aravind Krishna ◽  
S. Aadhishwaran ◽  
John George

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sakthivel Murugan R. ◽  
Vinodh S.

Purpose This paper aims to optimize the process parameters of the fused deposition modelling (FDM) process using the Grey-based Taguchi method and the results to be verified based on a technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) calculation. Design/methodology/approach The optimization of process parameters is gaining a potential role to develop robust products. In this context, this paper presents the parametric optimization of the FDM process using Grey-based Taguchi, TOPSIS and AHP method. The effect of slice height (SH), part fill style (PFS) and build orientation (BO) are investigated with the response parameters machining time, surface roughness and hardness (HD). Multiple objective optimizations were performed with weights of w1 = 60%, w2 = 20% and w3 = 20%. The significance of the process parameters over response parameters is identified through analysis of variance (ANOVA). Comparisons are made in terms of rank order with respect to grey relation grade (GRG), relative closeness and AHP index values. Response table, percentage contributions of process parameters for both GRG and TOPSIS evaluation are done. Findings The optimum factor levels are identified using GRG via the Grey Taguchi method and TOPSIS via relative closeness values. The optimized factor levels are SH (0.013 in), PFS (solid) and BO (45°) using GRG and SH (0.013 in), PFS (sparse-low density) and BO (45°) using TOPSIS relative closeness value. SH has higher significance in both Grey relational analysis and TOPSIS which were analysed using ANOVA. Research limitations/implications In this research, the multiple objective optimizations were done on an automotive component using GRG, TOPSIS and AHP which showed a 27% similarity in their ranking order among the experiments. In the future, other advanced optimization techniques will be applied to further improve the similarity in ranking order. Practical implications The study presents the case of an automotive component, which illustrates practical relevance. Originality/value In several research studies, optimization was done on the standard test specimens but not on a real-time component. Here, the multiple objective optimizations were applied to a case automotive component using Grey-based Taguchi and verified with TOPSIS. Hence, an effort has been taken to find optimum process parameters on FDM, for achieving smooth, hardened automotive components with enhanced printing time. The component can be explored as a replacement for the existing product.


2009 ◽  
Vol 01 (02) ◽  
pp. 89-97 ◽  
Author(s):  
Samir Kumar PANDA ◽  
Saumyakant PADHEE ◽  
Anoop Kumar SOOD ◽  
S. S. MAHAPATRA

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