scholarly journals Multi Objective Optimization of Fused Deposition Modeling Parameters for PC/ABS Blend Material Parts using GRA

2020 ◽  
Vol 9 (3) ◽  
pp. 1107-1116
Keyword(s):  
Layer Thickness ◽  
Fused Deposition Modeling ◽  
Experimental Result ◽  
Multi Objective Optimization ◽  
Support Structure ◽  
Multi Objective ◽  
Fused Deposition ◽  
Build Time ◽  
Deposition Modeling ◽  
Printing Speed

In this research, multi objective optimization is done on Fused Deposition Modeling (FDM) printing machine for Polycarbonate/Acrylonitrile Butadiene Styrene (PC/ABS) blend material parts. Reductions in part build time and material consumption without compromising its dimensional accuracy and mechanical properties are the major goals of many industries, because there is need to fulfil one part with multiple qualities. So that in this research, part printed without support structure by controlling five FDM process parameters at three levels such as layer thickness, raster width, extrusion temperature, bed temperature and printing speed by using Taguchi’s design of experiments method (L27 Orthogonal Array). This research can saves part build time, post processing time on support removal and damages occurred due to removal of support structure in part. For that, in this research effects of parameters are studied on surface roughness, build time, and flatness error of overhang structure of parts. Then Grey Relational Analysis (GRA) methodology is used for multi-objective optimization of FDM parameters to find best set of parameters for three responses. Analysis of Variance (ANOVA) is also used to find out significant parameters for multi responses and then confirmation test of experimental results also performed to verify the optimal settings of FDM parameters. The experimental result showed, layer thickness, raster width and part printing speed have the more significant effects on multiple performance characteristics.

scholarly journals Preparation of Hydrophobic Surface on PLA and ABS by Fused Deposition Modeling

Polymers ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1539 ◽  
Author(s):  
Huadong Yang ◽  
Fengchao Ji ◽  
Zhen Li ◽  
Shuai Tao
Keyword(s):  
Surface Roughness ◽  
Layer Thickness ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Hydrophobic Coatings ◽  
Fused Deposition ◽  
Filling Method ◽  
Deposition Modeling ◽  
Experiment Analysis ◽  
Printing Speed

In the fields of agriculture, medical treatment, food, and packaging, polymers are required to have the characteristics of self-cleaning, anti-icing, and anti-corrosion. The traditional preparation method of hydrophobic coatings is costly and the process is complex, which has special requirements on the surface of the part. In this study, fused deposition modeling (FDM) 3D printing technology with design and processing flexibility was applied to the preparation of hydrophobic coatings on polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS) parts, and the relationship between the printing process parameters and the surface roughness and wettability of the printed test parts was discussed. The experimental results show that the layer thickness and filling method have a significant effect on the surface roughness of the 3D-printed parts, while the printing speed has no effect on the surface roughness. The orthogonal experiment analysis method was used to perform the wettability experiment analysis, and the optimal preparation process parameters were found to be a layer thickness of 0.25 mm, the Grid filling method, and a printing speed of 150 mm/s.

Linear model analysis of fused deposition modeling process parameters for obtaining the maximum tensile strength in acrylonitrile butadiene styrene (ABS) and carbon fiber polylactic acid (PLA) materials

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Debashis Mishra ◽  
Anil Kumar Das
Keyword(s):  
Tensile Strength ◽  
Carbon Fiber ◽  
Layer Thickness ◽  
Process Parameters ◽  
Fused Deposition Modeling ◽  
Thermoplastic Material ◽  
Content Type ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Printing Speed

PurposeThe purpose of the experimental investigation was to optimize the process parameters of the fused deposition modeling (FDM) technique. The optimization of the process was performed to identify the relationship between the chosen factors and the tensile strength of acrylonitrile butadiene styrene (ABS) and carbon fiber polylactic acid (PLA) thermoplastic material, FDM printed specimens. The relationship was demonstrated by using the linear experimental model analysis, and a prediction expression was established. The developed prediction expression can be used for the prediction of tensile strength of selected thermoplastic materials at a 95% confidence level.Design/methodology/approachThe Taguchi L9 experimental methodology was used to plan the total number of experiments to be performed. The process parameters were chosen as three at three working levels. The working range of chosen factors was the printing speed (60, 80 and 100mm/min), 40%, 60% and 80% as the infill density and 0.1mm, 0.2mm and 0.3mm as the layer thickness. The fused deposition modeling process parameters were optimized to get the maximum tensile strength in FDM printed ABS and carbon fiber PLA thermoplastic material specimens.FindingsThe optimum condition was achieved by the process optimization, and the desired results were obtained. The maximum desirability was achieved as 0.98 (98%) for the factors, printing speed 100mm/min, infill density 60mm and layer thickness 0.3mm. The strength of the ABS specimen was predicted to be 23.83MPa. The observed strength value was 23.66MPa. The maximum desirability was obtained as 1 (100%) for the factors, printing speed 100mm/min, infill density 60mm and layer thickness 0.2mm. The strength of the carbon fiber PLA specimen was predicted to be 26.23MPa, and the obtained value was 26.49MPa.Research limitations/implicationsThe research shows the useful process parameters and their suitable working conditions to print the tensile specimens of the ABS and carbon fiber PLA thermoplastics by using the fused deposition modeling technique. The process was optimized to identify the most influential factor, and the desired optimum condition was achieved at which the maximum tensile strength was reported. The produced prediction expression can be used to predict the tensile strength of ABS and carbon fiber PLA filaments.Practical implicationsThe results obtained from the experimental investigation are useful to get an insight into the FDM process and working limits to print the parts by using the ABS and carbon fiber PLA material for various industrial and structural applications.Social implicationsThe results will be useful in choosing the suitable thermoplastic filament for the various prototyping and structural applications. The products that require freedom in design and are difficult to produce by most of the conventional techniques can be produced at low cost and in less time by the fused deposition modeling technique.Originality/valueThe process optimization shows the practical exposures to state an optimum working condition to print the ABS and carbon fiber PLA tensile specimens by using the FDM technique. The carbon fiber PLA shows better strength than ABS thermoplastic material.

scholarly journals The Synergic Effects of FDM 3D Printing Parameters on Mechanical Behaviors of Bronze Poly Lactic Acid Composites

2020 ◽  
Vol 4 (1) ◽  
pp. 17 ◽  
Author(s):  
Mahmoud Moradi ◽  
Mojtaba Karami Moghadam ◽  
Mahmoud Shamsborhan ◽  
Mahdi Bodaghi
Keyword(s):  
Layer Thickness ◽  
Fused Deposition Modeling ◽  
Corn Starch ◽  
Failure Load ◽  
Optimization Method ◽  
Poly Lactic Acid ◽  
Fused Deposition ◽  
Build Time ◽  
Optimization Parameters ◽  
Deposition Modeling

In this paper, the influence of layer thickness (LT), infill percentage (IP), and extruder temperature (ET) on the maximum failure load, thickness, and build time of bronze polylactic acid (Br-PLA) composites 3D printed by the fused deposition modeling (FDM) was investigated via an optimization method. PLA is a thermoplastic aliphatic polyester obtained from renewable sources, such as fermented plant starch, especially made by corn starch. The design of experiment (DOE) approach was used for optimization parameters, and 3D printings were optimized according to the applied statistical analyses to reach the best features. The maximum value of failure load and minimum value of the build time were considered as optimization criteria. Analysis of variance results identified the layer thickness as the main controlled variable for all responses. Optimum solutions were examined by experimental preparation to assess the efficiency of the optimization method. There was a superb compromise among experimental outcomes and predictions of the response surface method, confirming the reliability of predictive models. The optimum setting for fulfilling the first criterion could result in a sample with more than 1021 N maximum failure load. Finally, a comparison of maximum failure from PLA with Br-PLA was studied.

Assessing the effect of FDM processing parameters on mechanical properties of PLA parts using Taguchi method

2021 ◽  
pp. 089270572110530
Author(s):  
Nagarjuna Maguluri ◽  
Gamini Suresh ◽  
K Venkata Rao
Keyword(s):  
Mechanical Properties ◽  
Tensile Properties ◽  
Fused Deposition Modeling ◽  
Fracture Strain ◽  
Processing Parameters ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Nozzle Temperature ◽  
Experimental Runs ◽  
Printing Speed

Fused deposition modeling (FDM) is a fast-expanding additive manufacturing technique for fabricating various polymer components in engineering and medical applications. The mechanical properties of components printed with the FDM method are influenced by several process parameters. In the current work, the influence of nozzle temperature, infill density, and printing speed on the tensile properties of specimens printed using polylactic acid (PLA) filament was investigated. With an objective to achieve better tensile properties including elastic modulus, tensile strength, and fracture strain; Taguchi L8 array has been used for framing experimental runs, and eight experiments were conducted. The results demonstrate that the nozzle temperature significantly influences the tensile properties of the FDM printed PLA products followed by infill density. The optimum processing parameters were determined for the FDM printed PLA material at a nozzle temperature of 220°C, infill density of 100%, and printing speed of 20 mm/s.

Multi-objective optimization approach in design for additive manufacturing for fused deposition modeling

2019 ◽  
Vol 25 (5) ◽  
pp. 875-887
Author(s):  
Elnaz Asadollahi-Yazdi ◽  
Julien Gardan ◽  
Pascal Lafon
Keyword(s):  
Optimization Problem ◽  
Fused Deposition Modeling ◽  
Topological Optimization ◽  
Design For Additive Manufacturing ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Fused Deposition ◽  
Design And Manufacturing ◽  
Deposition Modeling ◽  
Manufacturing Parameters

Purpose This paper aims to provide a multi-objective optimization problem in design for manufacturing (DFM) approach for fused deposition modeling (FDM). This method considers the manufacturing criteria and constraints during the design by selecting the best manufacturing parameters to guide the designer and manufacturer in fabrication with FDM. Design/methodology/approach Topological optimization and bi-objective optimization problems are suggested to complete the DFM approach for design for additive manufacturing (DFAM) to define a product. Topological optimization allows the shape improvement of the product through a material distribution for weight gain based on the desired mechanical behavior. The bi-objective optimization problem plays an important role to evaluate the manufacturability by quantification and optimization of the manufacturing criteria and constraint simultaneously. Actually, it optimizes the production time, required material regarding surface quality and mechanical properties of the product because of two significant parameters as layer thickness and part orientation. Findings A comprehensive analysis of the existing DFAM approaches illustrates that these approaches are not developed sufficiently in terms of manufacturability evaluation in quantification and optimization levels. There is no approach that investigates the AM criteria and constraints simultaneously. It is necessary to provide a decision-making tool for the designers and manufacturers to lead to better design and manufacturing regarding the different AM characteristics. Practical implications To assess the efficiency of this approach, a wheel spindle is considered as a case study which shows how this method is capable to find the best design and manufacturing solutions. Originality/value A multi-criteria decision-making approach as the main contribution is developed to analyze FDM technology and its attributes, criteria and drawbacks. It completes the DFAM approach for FDM through a bi-objective optimization problem which deals with finding the best manufacturing parameters by optimizing production time and material mass because of the product mechanical properties and surface roughness.

scholarly journals Process Parameter Optimization in Fused Deposition Modeling (FDM) Using Response Surface Methodology (RSM)

2020 ◽  
Author(s):  
Muhammad Salman Mustafa ◽  
Muhammad Qasim Zafar ◽  
Muhammad Arslan Muneer ◽  
Muhammad Arif ◽  
Farrukh Arsalan Siddiqui ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Response Surface Methodology ◽  
Impact Strength ◽  
Response Surface ◽  
Layer Thickness ◽  
Fused Deposition Modeling ◽  
Experimental Results ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Printing Parameters

Abstract Fused Deposition Modeling (FDM) is a widely adopted additive manufacturing process to produce complex 3D structures and it is typically used in the fabrication of biodegradable materials e.g. PLA/PHA for biomedical applications. However, FDM as a fabrication process for such material needs to be optimized to enhance mechanical properties. In this study, dogbone and notched samples are printed with the FDM process to determine optimum values of printing parameters for superior mechanical properties. The effect of layer thickness, infill density, and print bed temperature on mechanical properties is investigated by applying response surface methodology (RSM). Optimum printing parameters are identified for tensile and impact strength and an empirical relation has been formulated with response surface methodology (RSM). Furthermore, the analysis of variance (ANOVA) was performed on the experimental results to determine the influence of the process parameters and their interactions. ANOVA results demonstrate that 44.7% infill density, 0.44 mm layer thickness, and 20C° printing temperatures are the optimum values of printing parameters owing to improved tensile and impact strength respectively. The experimental results were found in strong agreement with the predicted theoretical results.

Effect of process parameters on flexural strength and surface roughness in fused deposition modeling of PC-ABS material

2021 ◽  
pp. 251659842110311
Author(s):  
Shrikrishna Pawar ◽  
Dhananjay Dolas1
Keyword(s):  
Surface Roughness ◽  
Flexural Strength ◽  
Response Surface ◽  
Layer Thickness ◽  
Process Parameters ◽  
Surface Finish ◽  
Fused Deposition Modeling ◽  
Build Orientation ◽  
Fused Deposition ◽  
Deposition Modeling

Fused deposition modeling (FDM) is one of the most commonly used additive manufacturing (AM) technologies, which has found application in industries to meet the challenges of design modifications without significant cost increase and time delays. Process parameters largely affect the quality characteristics of AM parts, such as mechanical strength and surface finish. This article aims to optimize the parameters for enhancing flexural strength and surface finish of FDM parts. A total of 18 test specimens of polycarbonate (PC)-ABS (acrylonitrile–butadiene–styrene) material are printed to analyze the effect of process parameters, viz. layer thickness, build orientation, and infill density on flexural strength and surface finish. Empirical models relating process parameters with responses have been developed by using response surface regression and further analyzed by analysis of variance. Main effect plots and interaction plots are drawn to study the individual and combined effect of process parameters on output variables. Response surface methodology was employed to predict the results of flexural strength 48.2910 MPa and surface roughness 3.5826 µm with an optimal setting of parameters of 0.14-mm layer thickness and 100% infill density along with horizontal build orientation. Experimental results confirm infill density and build orientation as highly significant parameters for impacting flexural strength and surface roughness, respectively.

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