scholarly journals Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms

Materials ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7479
Author(s):  
Manjunath Patel Gowdru Chandrashekarappa ◽  
Ganesh Ravi Chate ◽  
Vineeth Parashivamurthy ◽  
Balakrishnamurthy Sachin Kumar ◽  
Mohd Amaan Najeeb Bandukwala ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Shell Thickness ◽  
Dimensional Accuracy ◽  
High Impact ◽  
Bald Eagle ◽  
Proper Function ◽  
Control Variables ◽  
Fused Deposition ◽  
High Impact Polystyrene ◽  
Cylindricity Error

High impact polystyrene (HIPS) material is widely used for low-strength structural applications. To ensure proper function, dimensional accuracy and porosity are at the forefront of industrial relevance. The dimensional accuracy cylindricity error (CE) and porosity of printed parts are influenced mainly by the control variables (layer thickness, shell thickness, infill density, print speed of the fused deposition modeling (FDM) process). In this study, a central composite design (CCD) matrix was used to perform experiments and analyze the complete insight information of the process (control variables influence on CE and porosity of FDM parts). Shell thickness for CE and infill density for porosity were identified as the most significant factors. Layer thickness interaction with shell thickness, infill density (except for CE), and print speed were found to be significant for both outputs. The interaction factors, i.e., shell thickness and infill density, were insignificant (negligible effect) for both outputs. The models developed produced a better fit for regression with an R2 equal to 94.56% for CE, and 99.10% for porosity, respectively. Four algorithms (bald eagle search optimization (BES), particle swarm optimization (PSO), RAO-3, and JAYA) were applied to determine optimal FDM conditions while examining six case studies (sets of weights assigned for porosity and CE) focused on minimizing both CE and porosity. BES and RAO-3 algorithms determined optimal conditions (layer thickness: 0.22 mm; shell thickness: 2 mm; infill density: 100%; print speed: 30 mm/s) at a reduced computation time equal to 0.007 s, differing from JAYA and PSO, which resulted in an experimental CE of 0.1215 mm and 2.5% of porosity in printed parts. Consequently, BES and RAO-3 algorithms are efficient tools for the optimization of FDM parts.

Dimensional Accuracy in PolyJet Printing: A Literature Review

2019 ◽  
Author(s):  
Ketan Thakare ◽  
Xingjian Wei ◽  
Zhijian Pei
Keyword(s):  
Additive Manufacturing ◽  
Layer Thickness ◽  
Surface Finish ◽  
Dimensional Accuracy ◽  
High Dimensional ◽  
Control Variables ◽  
Current Trends ◽  
Manufacturing Methods ◽  
Polyjet Printing ◽  
Part Orientation

Abstract PolyJet printing process is one of the additive manufacturing methods to print parts with high dimensional accuracy. To date, dimensional accuracies of such process have been investigated by a number of studies. This review will summarize those studies, and identify current trends. With respect to methods of measurements used in the reported studies, it is noted that no special preference is given to use of any method. In addition, the effects of four control variables of PolyJet process: part orientation, layer thickness, surface finish type and materials, on dimensional accuracy are noted based on the results of reported studies. There is consistency in results in studies considering control variables of layer thickness, surface finish type and materials. However, the results are inconsistent in studies considering part orientation.

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 Preparation and Evaluation of the Tensile Characteristics of Carbon Fiber Rod Reinforced 3D Printed Thermoplastic Composites

2020 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Arivazhagan Selvam ◽  
Suresh Mayilswamy ◽  
Ruban Whenish ◽  
Rajkumar Velu ◽  
Bharath Subramanian
Keyword(s):  
Tensile Strength ◽  
Carbon Fiber ◽  
Layer Thickness ◽  
Shell Thickness ◽  
Fused Deposition Modeling ◽  
Acrylonitrile Butadiene Styrene ◽  
Thermoplastic Composites ◽  
Critical Parameters ◽  
Fused Deposition ◽  
Deposition Modeling

The most common method to fabricate both simple and complex structures in the additive manufacturing process is fused deposition modeling (FDM). Many researchers have studied the strengthening of FDM components by adding short carbon fibers (CF) or by reinforcing solid carbon fiber rods. In the current research, we sought to enhance the mechanical properties of FDM components by adding bioinspired solid CF rods during the fabrication process. An effective bonding interface of bioinspired CF rods and polylactic acid (PLA) was achieved by triangular interlocking sutures and by employing synthetic glue as the binding agent. In particular, the tensile strength of solid CF rod reinforced PLA samples was studied. Critical parameters such as layer thickness, extruder temperature, extruder speed, and shell thickness were considered for optimization. Significant process parameters were identified through leverage plots using the response surface methodology (RSM). The optimum parameters were found to be layer thickness of 0.04 mm, extruder temperature of 215 °C, extruder speed of 60 mm/s, and shell thickness of 1.2 mm. The results revealed that the bioinspired solid CF rod reinforced PLA (CFRPLA) composite exhibited a tensile strength of 82.06 MPa, which was approximately three times higher than the pure PLA (28 MPa, 66% lower than CFRPLA), acrylonitrile butadiene styrene (ABS) (28 MPa, 66% lower than CFRPLA), polyethylene terephthalate glycol (PETG) (34 MPa, 60% lower than CFRPLA), and nylon (34 MPa, 60% lower than CFRPLA) samples.

Optimasi Parameter Proses 3D Printing FDM Terhadap Akurasi Dimensi Menggunakan Filament Eflex

2019 ◽  
Vol 11 (01) ◽  
pp. 33-40
Author(s):  
Pristiansyah Pristiansyah ◽  
Hasdiansah Hasdiansah ◽  
Sugiyarto Sugiyarto
Keyword(s):  
3D Printing ◽  
Layer Thickness ◽  
Dimensional Accuracy ◽  
Process Parameter ◽  
Material Research ◽  
Fused Deposition ◽  
Flexible Materials ◽  
Flexible Material ◽  
Fan Speed ◽  
Nozzle Temperature

Fused Deposition Modeling (FDM) is a 3D Printing technique used to print products using filaments as material. The printed product has ideal geometric characteristics if it has meticulous size and perfect shape. One type of material that can be processed using 3D Printing FDM is flexible material. Research in terms of dimensional accuracy has been carried out on PLA and ABS materials. While research using flexible materials is still rarely done. From these problems, we need a study to get the process parameter settings on a 3D Printer machine that is optimal in obtaining dimensional accuracy using flexible materials. The research was carried out using the Prusa model DIY (Do It Yourself) 3D machine with FDM technology. The material used is Eflex type flexible filament with a diameter of 1.75 mm. The process parameters used in this study are flowrate, layer thickness, temperature nozzle, speed printing, overlap, and fan speed. Cuboid test specimens measuring 20 mm × 20 mm × 20 mm. Process parameter optimization using the Taguchi L27 Orthogonal Array method for dimensional accuracy testing. Optimal process parameter values for obtaining X dimension accuracy are 110% flowrate, 0.10 mm layer thickness, 210 °C nozzle temperature, 40 mm/s print speed, 75% overlap, and 50% fan speed. Y dimension is 120% flowrate, layer thickness 0.20 mm, nozzle temperature 230 °C, print speed 30 mm/s, overlap 75%, and fan speed 100%. As well as the Z dimension is 120% flowrate, layer thickness 0.30 mm, nozzle temperature 210 °C, print speed 30 mm/s, overlap 50%, and fan speed 100%.

scholarly journals Multi-Response Optimization of Process Parameter in Fused Deposition Modelling by Response Surface Methodology

2019 ◽  
Vol 8 (3) ◽  
pp. 327-338 ◽  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Ambient Temperature ◽  
Response Surface ◽  
Layer Thickness ◽  
Dimensional Accuracy ◽  
Fused Deposition Modelling ◽  
Cross Sectional ◽  
Factors Affecting ◽  
Fused Deposition

This paper reported on the effect of ambient temperature, layer thickness, and part angle on the surface roughness and dimensional accuracy. The response surface methodology (RSM) was employed by using historical data in the experiment to determine the significant factors and their interactions on the fused deposition modelling (FDM) performance. Three controllable variables namely ambient temperature (30 °C, 45 °C, 60 °C), layer thickness (0.178 mm, 0.267 mm, 0.356 mm) and part angle (22.5°, 45°, 67.5°) have been studied. A total of 29 numbers of experiments had been conducted, including two replications at the center point. The results showed that all the parameter variables have significant effects on the part surface roughness and dimensional accuracy. Layer thickness is the most dominant factors affecting surface roughness. Meanwhile, the ambient temperature was the most dominant in determining part dimensional accuracy. The responses of various factors had been illustrated in the cross-sectional sample analysis. The optimum parameter required for minimum surface roughness and dimensional accuracy was at ambient temperature 30 °C, layer thickness 0.18 mm and part angle 67.38°. The optimization has produced maximum productivity with RaH 3.21 µm, RaV 11.78 µm, and RaS 12.79 µm. Meanwhile, dimensional accuracy height eror 3.21%, width error 3.70% and angle 0.38°

scholarly journals Optimisation of Strength Properties of FDM Printed Parts—A Critical Review

Polymers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1587
Author(s):  
Daniyar Syrlybayev ◽  
Beibit Zharylkassyn ◽  
Aidana Seisekulova ◽  
Mustakhim Akhmetov ◽  
Asma Perveen ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Layer Thickness ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Complex Geometry ◽  
Positive Impact ◽  
Dimensional Accuracy ◽  
Strength Properties ◽  
Fused Filament Fabrication ◽  
Fused Deposition

Additive Manufacturing is currently growing fast, especially fused deposition modeling (FDM), also known as fused filament fabrication (FFF). When manufacturing parts use FDM, there are two key parameters—strength of the part and dimensional accuracy—that need to be considered. Although FDM is a popular technology for fabricating prototypes with complex geometry and other part product with reduced cycle time, it is also limited by several drawbacks including inadequate mechanical properties and reduced dimensional accuracy. It is evident that part qualities are greatly influenced by the various process parameters, therefore an extensive review of the effects of the following process parameters was carried out: infill density, infill patterns, extrusion temperature, layer thickness, nozzle diameter, raster angle and build orientation on the mechanical properties. It was found from the literature that layer thickness is the most important factor among the studied ones. Although manipulation of process parameters makes significant differences in the quality and mechanical properties of the printed part, the ideal combination of parameters is challenging to achieve. Hence, this study also includes the influence of pre-processing of the printed part to improve the part strength and new research trends such as, vacuum-assisted FDM that has shown to improve the quality of the printing due to improved bonding between the layers. Advances in materials and technologies that are currently under development are presented. For example, the pre-deposition heating method, using an IR lamp of other technologies, shows a positive impact on the mechanical properties of the printed parts.

Evaluation of FDM Pattern with ABS and PLA Material

2013 ◽  
Vol 465-466 ◽  
pp. 55-59 ◽  
Author(s):  
M.N. Hafsa ◽  
Mustaffa Ibrahim ◽  
Md. Saidin Wahab ◽  
M.S. Zahid
Keyword(s):  
Surface Roughness ◽  
Layer Thickness ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Acrylonitrile Butadiene Styrene ◽  
Casting Process ◽  
Fused Deposition ◽  
Before And After ◽  
High Layer ◽  
Better Than

Selection of the most suitable Rapid Prototyping (RP) and manufacturing process for a specific part creation is a difficult task due to the development of RP processes and materials. Most current RP processes can build with more than one type of material. The paper presents the evaluation on Acrylonitrile Butadiene Styrene (ABS) and Polylactic acid (PLA) part produced from Fused Deposition Modeling (FDM) as a master pattern for Investment Casting (IC) process. The main purpose of this research is to evaluate the dimensional accuracy and surface roughness for hollow and solid part of FDM pattern for IC process with different layer thickness. The value were taken for both before and after the casting process. Results show that model fabricated with hollow internal pattern structure (ABS material) that produced by low layer thickness is better than other models in terms of its dimensional accuracy (-0.19666mm) and surface roughness (1.41μm). Even though the ABS built part performed better as the model, the PLA build part produces better overall casting result. Final part fabricated with solid pattern (PLA material) that produced by high layer thickness is better than other final parts which its dimensional accuracy (-0.12777mm) and surface roughness (3.07μm).

Experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling

2020 ◽  
Vol 26 (9) ◽  
pp. 1535-1554
Author(s):  
Swapnil Vyavahare ◽  
Shailendra Kumar ◽  
Deepak Panghal
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Layer Thickness ◽  
Process Parameters ◽  
Dimensional Accuracy ◽  
Fused Deposition Modelling ◽  
Content Type ◽  
Build Orientation ◽  
Fused Deposition ◽  
Significant Process

Purpose This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM) technique of additive manufacturing. The fabricated parts of acrylonitrile butadiene styrene (ABS) material have pyramidal and conical features. Influence of five process parameters of FDM, namely, layer thickness, wall print speed, build orientation, wall thickness and extrusion temperature is studied on response characteristics. Furthermore, regression models for responses are developed and significant process parameters are optimized. Design/methodology/approach Comprehensive experimental study is performed using response surface methodology. Analysis of variance is used to investigate the influence of process parameters on surface roughness, dimensional accuracy and time of fabrication in both outer pyramidal and inner conical regions of part. Furthermore, a multi-response optimization using desirability function is performed to minimize surface roughness, improve dimensional accuracy and minimize time of fabrication of parts. Findings It is found that layer thickness and build orientation are significant process parameters for surface roughness of parts. Surface roughness increases with increase in layer thickness, while it decreases initially and then increases with increase in build orientation. Layer thickness, wall print speed and build orientation are significant process parameters for dimensional accuracy of FDM parts. For the time of fabrication, layer thickness and build orientation are found as significant process parameters. Based on the analysis, statistical non-linear quadratic models are developed to predict surface roughness, dimensional accuracy and time of fabrication. Optimization of process parameters is also performed using desirability function. Research limitations/implications The present study is restricted to the parts of ABS material with pyramidal and conical features only fabricated on FDM machine with delta configuration. Originality/value From the critical review of literature it is found that some researchers have made to study the influence of few process parameters on surface roughness, dimensional accuracy and time of fabrication of simple geometrical parts. Also, regression models and optimization of process parameters has been performed for simple parts. The present work is focussed on studying all these aspects in complicated geometrical parts with pyramidal and conical features.

OPTIMALISASI KEKUATAN BENDING HASIL 3D PRINTING MENGGUNAKAN METODE RESPONSE SURFACE PADA FILAMEN PLA (POLY LACTIC ACID)

2021 ◽  
Vol 3 (3) ◽  
pp. 58-66
Author(s):  
Dira Nurfaedah ◽  
Rifelino Rifelino ◽  
Purwantono Purwantono ◽  
Febri Prasetya
Keyword(s):  
Tensile Strength ◽  
Lactic Acid ◽  
Layer Thickness ◽  
Shell Thickness ◽  
Bending Strength ◽  
Poly Lactic Acid ◽  
Fused Deposition Modelling ◽  
Fused Deposition ◽  
Nozzle Temperature ◽  
Deposition Angle

Akhir-akhir ini teknologi baru sudah mengembangkan produksi banyak meragup keuntungan untuk yang membutuhkan teknologi past prototype. Printer 3D merupakan teknologi past prototyping yang salah satu jenisnya ialah FDM (Fused Deposition Modelling) yang terkenal dan terjangkau. PLA memiliki karakteristik transparan, bersifat kaku, berbentuk butiran, memiliki ketahanan terhadap kelembapan serta polimer yang elastis. Pada PLA nozzle temperature dan layer thickness berpengaruh terhadap keelastisitas produk. pengaruh ketebalan lapisan cetak, shell thickness mendapatkan parameter paling mendominasi pada respon tensile strength. Akan tetapi dalam hal flexural strength dari bahan PLA, parameter ketebalan lapis, deposition angle, dan pola infil, dikonfimasi ketebalan lapis yang sangat memberikan pengaruh pada bending strength bahan. Metode permukaan respon merupakan sekumpulan statistika serta kalkulasi teknik dimana berfungsi meningkatkan serta memaksimalkan proses, yang mana banyak parameter bebas mempengaruhi variabel respon. Kekuatan bending tertinggi berada pada parameter layer thickness 0.3 mm, nozzle temperature 205oC, dan infill percentage 30% dengan 71.605 MPa. Pada penelitian ini variabel layer thickness sangat berpengaruh terhadap kekuatan bending, nozzle temperature dan infill percentage tidak terlalu berpengaruh terhadap kekuatan bending. Dalam penentuan nilai optimum berdasarkan hasil analisis varian model orde 2 dengan redidual identik menyebar secara acak dan titik residual mendekati garis diagonal untuk uji kenormalan yang berarti memiliki kontribusi terhadap model. Nilai optimum dari variabel bebas menghasilkan nilai bending strength optimal yaitu 0.3 mm untuk layer thickness, 208,18oC untuk nozzle temperature dan 30% untuk infill percentage dengan bending strength yang paling optimal adalah 72,0443 MPa.

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