scholarly journals Mathematical Modeling and Optimization of Fused Filament Fabrication (FFF) Process Parameters for Shape Deviation Control of Polyamide 6 Using Taguchi Method

Polymers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3697
Author(s):  
Zohreh Shakeri ◽  
Khaled Benfriha ◽  
Mohammadali Shirinbayan ◽  
Mohammad Ahmadifar ◽  
Abbas Tcharkhtchi
Keyword(s):  
Product Development ◽  
Process Parameters ◽  
Optimization Method ◽  
Polyamide 6 ◽  
Wall Layer ◽  
Layer By Layer ◽  
Fused Filament Fabrication ◽  
Taguchi Optimization ◽  
Shape Deviation ◽  
Layer Height

Fused filament fabrication (FFF) is a layer-by-layer additive manufacturing (AM) process for producing parts. For industries to gain a competitive advantage, reducing product development cycle time is a basic goal. As a result, industries’ attention has turned away from traditional product development processes toward rapid prototyping techniques. Because different process parameters employed in this method significantly impact the quality of FFF manufactured parts, it is essential to optimize FFF process parameters to enhance component quality. The paper presents optimization of fused filament fabrication process parameters to improve the shape deviation such as cylindricity and circularity of 3D printed parts with the Taguchi optimization method. The effect of thickness, infill pattern, number of walls, and layer height was investigated as variable parameters for experiments on cylindricity and circularity. The MarkForged® used Nylon White (PA6) to create the parts. ANOVA and the S/N ratio are also used to evaluate and optimize the influence of chosen factors. As a result, it was concluded that the hexagonal infill pattern, the thickness of 5 mm, wall layer of 2, and a layer height of 1.125 mm were known to be the optimal process parameters for circularity and cylindricity in experiments. Then a linear regression model was created to observe the relationship between the control variables with cylindricity and circularity. The results were confirmed by a confirmation test.

scholarly journals The Impact of 3D Printing Process Parameters on the Dielectric Properties of High Permittivity Composites

Designs ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. 50 ◽  
Author(s):  
Athanasios Goulas ◽  
Shiyu Zhang ◽  
Darren A. Cadman ◽  
Jan Järveläinen ◽  
Ville Mylläri ◽  
...  
Keyword(s):  
3D Printing ◽  
Process Parameters ◽  
Relative Permittivity ◽  
Main Process ◽  
Fused Filament Fabrication ◽  
Layer Height ◽  
Additive Manufacturing Technology ◽  
The Impact ◽  
Printing Speed ◽  
Hatch Spacing

Fused filament fabrication (FFF) is a well-known and greatly accessible additive manufacturing technology, that has found great use in the prototyping and manufacture of radiofrequency componentry, by using a range of composite thermoplastic materials that possess superior properties, when compared to standard materials for 3D printing. However, due to their nature and synthesis, they are often a great challenge to print successfully which in turn affects their microwave properties. Hence, determining the optimum printing strategy and settings is important to advance this area. The manufacturing study presented in this paper shows the impact of the main process parameters: printing speed, hatch spacing, layer height and material infill, during 3D printing on the relative permittivity (εr), and loss tangent (tanδ) of the resultant additively manufactured test samples. A combination of process parameters arising from this study, allowed successful 3D printing of test samples, that marked a relative permittivity of 9.06 ± 0.09 and dielectric loss of 0.032 ± 0.003.

scholarly journals Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology

Polymers ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 4152
Author(s):  
Carmelo J. Luis-Pérez ◽  
Irene Buj-Corral ◽  
Xavier Sánchez-Casas
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Desirability Function ◽  
Nozzle Diameter ◽  
Simultaneous Optimization ◽  
Acetabular Cup ◽  
Fused Filament Fabrication ◽  
Dimensional Error ◽  
Layer Height ◽  
Form Errors

As is widely known, additive manufacturing (AM) allows very complex parts to be manufactured with porous structures at a relatively low cost and in relatively low manufacturing times. However, it is necessary to determine in a precise way the input values that allow better results to be obtained in terms of microgeometry, form errors, and dimensional error. In an earlier work, the influence of the process parameters on surface roughness obtained in fused filament fabrication (FFF) processes was analyzed. This present study focuses on form errors as well as on dimensional error of hemispherical cups, with a similar shape to that of the acetabular cup of hip prostheses. The specimens were 3D printed in polylactic acid (PLA). Process variables are nozzle diameter, temperature, layer height, print speed, and extrusion multiplier. Their influence on roundness, concentricity, and dimensional error is considered. To do this, adaptive neuro-fuzzy inference systems (ANFIS) models were used. It was observed that dimensional error, roundness, and concentricity depend mainly on the nozzle diameter and on layer height. Moreover, high nozzle diameter of 0.6 mm and high layer height of 0.3 mm are not recommended. A desirability function was employed along with the ANFIS models in order to determine the optimal manufacturing conditions. The main aim of the multi-objective optimization study was to minimize average surface roughness (Ra) and roundness, while dimensional error was kept within the interval Dimensional Error≤0.01. When the simultaneous optimization of both the internal and the external surface of the parts is performed, it is recommended that a nozzle diameter of 0.4 mm be used, to have a temperature of 197 °C, a layer height of 0.1 mm, a print speed of 42 mm/s, and extrusion multiplier of 94.8%. This study will help to determine the influence of the process parameters on the quality of the manufactured parts.

Optimization of Plastic Injection Molding Process Parameters for Thin-Wall Plastics Injection Molding

2009 ◽  
Vol 69-70 ◽  
pp. 525-529 ◽  
Author(s):  
Jie Jin ◽  
H.Y. Yu ◽  
S. Lv
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Optimization Method ◽  
Injection Molding Process ◽  
Thin Wall ◽  
Molding Process ◽  
Taguchi Optimization ◽  
Taguchi Optimization Method ◽  
Plastics Injection Molding ◽  
Injection Molded

The effects of the process parameters on the warpge and shrinkage of parts in different thickness are analyzed by Taguchi optimization method. Taguchi optimization method was used for exploiting mold analysis based on three level factorial designs. Orthogonal arrays of Taguchi, the signal-to-noise (S/N) ratio, the analysis of variance (ANOVA) are utilized to find the optimal levels and the effect of process parameters on warpage. It can be concluded that Taguchi method is suitable to solve the quality problem of the injection-molded thermoplastic parts.

scholarly journals Taguchi optimization and scale up of xylanase from Bacillus licheniformis isolated from hot water geyser

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Girisha Malhotra ◽  
Shilpa S. Chapadgaonkar
Keyword(s):  
Process Parameters ◽  
Wheat Bran ◽  
Scale Up ◽  
Industrial Applications ◽  
Hot Water ◽  
Optimization Strategy ◽  
Taguchi Optimization ◽  
Xylanase Production ◽  
Alkali Tolerance ◽  
Optimized Conditions

Abstract Background Xylanase is one of the widely applied industrial enzymes with diverse applications. Thermostability and alkali tolerance are the two most desirable qualities for industrial applications of xylanase. In this paper, we reveal the statistical Taguchi optimization strategy for maximization of xylanase production. The important process parameters pH, temperature, concentration of wheat bran, and concentration of yeast extract were optimized using the Taguchi L8 orthogonal array where the 4 factors were considered at 2 levels (high and low). Results The optimized conditions given by model were obtained as follows: (i) pH 6, (ii) culture temperature 35 °C, (iii) concentration of xylan 2% w/v, (iv) concentration of wheat bran 2.5% w/v. The production was scaled upto 2.5 L bioreactor using optimized process parameters. A high xylanase titer of 400 U/ml could be achieved in less than 60 h of culture in the reactor. Conclusion Optimization was successful in achieving about threefold increase in the yield of xylanase. The optimized conditions resulted in a successful scale up and enhancement of xylanase production.

scholarly journals Optimization of a 3D-Printed Permanent Magnet Coupling Using Genetic Algorithm and Taguchi Method

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 494
Author(s):  
Ekaterina Andriushchenko ◽  
Ants Kallaste ◽  
Anouar Belahcen ◽  
Toomas Vaimann ◽  
Anton Rassõlkin ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Permanent Magnet ◽  
Optimization Problems ◽  
Optimization Method ◽  
Taguchi Optimization ◽  
Torque Density ◽  
Electromagnetic Devices ◽  
3D Printed ◽  
Manufacturing Techniques

In recent decades, the genetic algorithm (GA) has been extensively used in the design optimization of electromagnetic devices. Despite the great merits possessed by the GA, its processing procedure is highly time-consuming. On the contrary, the widely applied Taguchi optimization method is faster with comparable effectiveness in certain optimization problems. This study explores the abilities of both methods within the optimization of a permanent magnet coupling, where the optimization objectives are the minimization of coupling volume and maximization of transmitted torque. The optimal geometry of the coupling and the obtained characteristics achieved by both methods are nearly identical. The magnetic torque density is enhanced by more than 20%, while the volume is reduced by 17%. Yet, the Taguchi method is found to be more time-efficient and effective within the considered optimization problem. Thanks to the additive manufacturing techniques, the initial design and the sophisticated geometry of the Taguchi optimal designs are precisely fabricated. The performances of the coupling designs are validated using an experimental setup.

scholarly journals Metallization of Thermoplastic Polymers and Composites 3D Printed by Fused Filament Fabrication

Technologies ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 49
Author(s):  
Alessia Romani ◽  
Andrea Mantelli ◽  
Paolo Tralli ◽  
Stefano Turri ◽  
Marinella Levi ◽  
...  
Keyword(s):  
Physical Vapor Deposition ◽  
Test Sample ◽  
Tensile Tests ◽  
Layer By Layer ◽  
Post Processing ◽  
Thermoplastic Polymers ◽  
Fused Filament Fabrication ◽  
Scanning Calorimetry ◽  
3D Printed ◽  
Manufacturing Technologies

Fused filament fabrication allows the direct manufacturing of customized and complex products although the layer-by-layer appearance of this process strongly affects the surface quality of the final parts. In recent years, an increasing number of post-processing treatments has been developed for the most used materials. Contrarily to other additive manufacturing technologies, metallization is not a common surface treatment for this process despite the increasing range of high-performing 3D printable materials. The objective of this work is to explore the use of physical vapor deposition sputtering for the chromium metallization of thermoplastic polymers and composites obtained by fused filament fabrication. The thermal and mechanical properties of five materials were firstly evaluated by means of differential scanning calorimetry and tensile tests. Meanwhile, a specific finishing torture test sample was designed and 3D printed to perform the metallization process and evaluate the finishing on different geometrical features. Furthermore, the roughness of the samples was measured before and after the metallization, and a cost analysis was performed to assess the cost-efficiency. To sum up, the metallization of five samples made with different materials was successfully achieved. Although some 3D printing defects worsened after the post-processing treatment, good homogeneity on the finest details was reached. These promising results may encourage further experimentations as well as the development of new applications, i.e., for the automotive and furniture fields.

scholarly journals Fused Deposition Modelling of Fibre Reinforced Polymer Composites: A Parametric Review

2021 ◽  
Vol 5 (1) ◽  
pp. 29
Author(s):  
Narongkorn Krajangsawasdi ◽  
Lourens G. Blok ◽  
Ian Hamerton ◽  
Marco L. Longana ◽  
Benjamin K. S. Woods ◽  
...  
Keyword(s):  
Process Parameters ◽  
Mechanical Performance ◽  
Fibre Length ◽  
Processing Parameters ◽  
Thermoplastic Composite ◽  
Fused Deposition Modelling ◽  
Layer By Layer ◽  
Fused Deposition ◽  
Fibre Reinforced Polymer ◽  
Printing Parameters

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.

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