Effects of Process Parameters on Surface Roughness, Dimensional Accuracy and Printing Time in 3D Printing

2020 ◽  
pp. 187-197
Author(s):  
Rajat Jain ◽  
Shivansh Nauriyal ◽  
Vishal Gupta ◽  
Kanwaljit Singh Khas
Keyword(s):  
Surface Roughness ◽  
3D Printing ◽  
Process Parameters ◽  
Dimensional Accuracy ◽  
Printing Time

scholarly journals Experiment-Based Process Modeling and Optimization for High-Quality and Resource-Efficient FFF 3D Printing

2020 ◽  
Vol 10 (8) ◽  
pp. 2899 ◽  
Author(s):  
Ahmed Elkaseer ◽  
Stella Schneider ◽  
Steffen G. Scholz
Keyword(s):  
Surface Roughness ◽  
Energy Consumption ◽  
3D Printing ◽  
Layer Thickness ◽  
Process Parameters ◽  
Inclination Angle ◽  
Dimensional Accuracy ◽  
Surface Inclination ◽  
Thick Layers ◽  
Printing Speed

This article reports on the investigation of the effects of process parameters and their interactions on as-built part quality and resource-efficiency of the fused filament fabrication 3D printing process. In particular, the influence of five process parameters: infill percentage, layer thickness, printing speed, printing temperature, and surface inclination angle on dimensional accuracy, surface roughness of the built part, energy consumption, and productivity of the process was examined using Taguchi orthogonal array (L50) design of experiment. The experimental results were analyzed using ANOVA and statistical analysis, and the parameters for optimal responses were identified. Regression models were developed to predict different process responses in terms of the five process parameters experimentally examined in this study. It was found that dimensional accuracy is negatively influenced by high values of layer thickness and printing speed, since thick layers of printed material tend to spread out and high printing speeds hinder accurate deposition of the printed material. In addition, the printing temperature, which regulates the viscosity of the used material, plays a significant role and helps to minimize the dimensional error caused by thick layers and high printing speeds, whereas the surface roughness depends very much on surface inclination angle and layer thickness, which together determine the influence of the staircase effect. Energy consumption and productivity are primarily affected by printing speed and layer thickness, due to their high correlation with build time.

scholarly journals Dimensional accuracy and surface roughness of polymeric dental bridges produced by different 3D printing processes

2018 ◽  
Vol 2 (94) ◽  
pp. 65-75 ◽  
Author(s):  
T.D. Dikova ◽  
D.A. Dzhendov ◽  
D. Ivanov ◽  
K. Bliznakova
Keyword(s):  
Surface Roughness ◽  
3D Printing ◽  
Fused Deposition Modeling ◽  
New Technologies ◽  
Dimensional Accuracy ◽  
Average Roughness ◽  
Training Models ◽  
Fused Deposition ◽  
3D Printers ◽  
Materials Used

Purpose: To compare the dimensions accuracy and surface roughness of polymeric dental bridges produced by different 3D printers. Design/methodology/approach: Four-part dental bridges were manufactured by three printing systems working on the basis of digital light projection (DLP) stereolithography (SLA), laser-assisted SLA and fused deposition modeling (FDM). The materials used from SLA printers are liquid methacrylate photopolymer resins, while FDM printer use thin wire plastic polylactic acid. The accuracy of the external dimensions of dental bridges was evaluated and the surface roughness was measured. Findings: It was found that compared to the base model, the dimensions of the SLA printed bridges are bigger with 1.25%-6.21%, while the corresponding dimensions of the samples, made by FDM are smaller by 1.07%-4.71%, regardless the position of the object towards the substrate. The samples, produced by FDM, are characterized with the highest roughness. The average roughness deviation (Ra) values for DLP SLA and lase-assisted SLA are 2.40 μm and 2.97 μm, respectively. Research limitations/implications: For production of high quality polymeric dental constructions next research should be targeted to investigation of the polymerization degree, stresses and deformations. Practical implications: Our study shows that 3D printers, based on laser-assisted and DLP SLA, can be successfully used for manufacturing of polymeric dental bridges – temporary restorations or cast patterns, while FDM system is more suitable for training models. The results will help the dentists to make right choice of the most suitable 3D printer. Originality/value: One of the largest fixed partial dentures – four-part bridges, produced by three different commercial 3D printing systems, were investigated by comparative analysis. The paper will attract readers’ interest in the field of biomedical materials and application of new technologies in dentistry.

Experimental investigation on the effect of laser powder bed fusion process variables on dimensional accuracy, surface roughness and cylindricity of the AlSi10Mg alloy component

2021 ◽  
pp. 095440892110390
Author(s):  
Nagendra K Maurya ◽  
Ashish K Srivastava ◽  
Ambuj Saxena ◽  
Shashi P Dwivedi ◽  
Mashood Ashraf Ali ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Linear Dimension ◽  
Dimensional Accuracy ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Process Variables ◽  
Connecting Rod ◽  
Powder Bed ◽  
Response Variables

The present study deals with the influence of laser powder bed fusion process parameters on the selected linear dimension, surface roughness and cylindricity of AlSi10Mg alloy for manufacturing of a prototype connecting rod. The process variables used in this investigation are laser power, laser velocity, layer thickness and scanning speed. Response surface methodology is used to perform experiments and data analysis. The levels of process parameters are same that is, five for all the selected input process variables. An automotive component connecting rod is used as a component to analyze the effect of process variables on selected response variables. The optimum sating of process variables are different for dimensional accuracy, surface roughness and cylindricity. Minitab 14 software is used for the data analysis. The international tolerance grades of confirmation experiments are calculated as per the ISO standard UNI EN 20286-I and DIN 16901. A quadratic regression models are developed to estimate the response variables in terms of process parameters. The model is adequate within the experimental domain. X-chart of confirmation experiments is plotted. The deviation in the linear dimension is within the limit of ±3 sigma (σ). The lowest values of response variables at the best level of process parameters are obtained, that is, percentage error in dimensional accuracy of 2.65%, surface roughness of 2.57 µm and cylindricity of 0.09 mm. The novelty of this work lies in the fact that only a few studies have been conducted related to the form errors in the archival literature.

Multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components

2017 ◽  
Vol 23 (5) ◽  
pp. 845-857 ◽  
Author(s):  
Parlad Kumar Garg ◽  
Rupinder Singh ◽  
IPS Ahuja
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Surface Finish ◽  
Dimensional Accuracy ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Fused Deposition ◽  
Taguchi Design Of Experiments ◽  
Investment Cast

Purpose The purpose of this paper is to optimize the process parameters to obtain the best dimensional accuracy, surface finish and hardness of the castings produced by using fused deposition modeling (FDM)-based patterns in investment casting (IC). Design/methodology/approach In this paper, hip implants have been prepared by using plastic patterns in IC process. Taguchi design of experiments has been used to study the effect of six different input process parameters on the dimensional deviation, surface roughness and hardness of the implants. Analysis of variance has been used to find the effect of each input factor on the output. Multi-objective optimization has been done to find the combined best values of output. Findings The results proved that the FDM patterns can be used successfully in IC. A wax coating on the FDM patterns improves the surface finish and dimensional accuracy. The improved dimensional accuracy, surface finish and hardness have been achieved simultaneously through multi-objective optimization. Research limitations/implications A thin layer of wax is used on the plastic patterns. The effect of thickness of the layer has not been considered. Further research is needed to study the effect of the thickness of the wax layer. Practical implications The results obtained by the study would be helpful in making decisions regarding machining and/or coating on the parts produced by this process. Originality/value In this paper, multi-objective optimization of dimensional accuracy, surface roughness and hardness of hybrid investment cast components has been performed.

Effects of Wire-EDM Machining Variables on Surface Roughness of D2 Steel Material

2019 ◽  
Vol 969 ◽  
pp. 656-661 ◽  
Author(s):  
Ramesh Rudrapati ◽  
Lakhan Rathod
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Electrical Discharge Machining ◽  
Dimensional Accuracy ◽  
Cuckoo Search ◽  
Industrial Applications ◽  
Correct Selection ◽  
Steel Material ◽  
D2 Steel ◽  
Experimental Runs

Newly developed D2 steel is widely used for various advanced engineering applications. Machining of D2 steel to obtain desired quality responses has immense importance for the effective utilization of these materials for advanced industrial applications like aerospace, marine, automobile, etc. Wire electrical discharge machining (WEDM) is used to machine difficult to machine materials and to produce sophisticated features with better dimensional accuracy. Obtaining the fine surface roughness in WEDM has highly depends on correct selection of process parameters. In the present work, experimental investigation was planned to study the effects of WEDM input parameters on surface roughness (Ra) of D2 steel. Experimental runs were conducted by using L16 orthogonal array of Taguchi method. The analysis of variance was employed to determine the influences of process parameters on Ra. Response surface methodology (RSM) and cuckoo search optimization (CSO) algorithm had been used to model and optimize the surface roughness. From the study, it was found that Ra value had improved as compared to initial experimental runs.

scholarly journals Effect of Selective Laser Melting Process Parameters on the Quality of Al Alloy Parts: Powder Characterization, Density, Surface Roughness, and Dimensional Accuracy

Materials ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 2343 ◽  
Author(s):  
Ahmed Maamoun ◽  
Yi Xue ◽  
Mohamed Elbestawi ◽  
Stephen Veldhuis
Keyword(s):  
Surface Roughness ◽  
Selective Laser Melting ◽  
Process Parameters ◽  
Dimensional Accuracy ◽  
High Strength ◽  
Melting Process ◽  
Al Alloys ◽  
Al Alloy ◽  
Laser Melting

Additive manufacturing (AM) of high-strength Al alloys promises to enhance the performance of critical components related to various aerospace and automotive applications. The key advantage of AM is its ability to generate lightweight, robust, and complex shapes. However, the characteristics of the as-built parts may represent an obstacle to the satisfaction of the parts’ quality requirements. The current study investigates the influence of selective laser melting (SLM) process parameters on the quality of parts fabricated from different Al alloys. A design of experiment (DOE) was used to analyze relative density, porosity, surface roughness, and dimensional accuracy according to the interaction effect between the SLM process parameters. The results show a range of energy densities and SLM process parameters for AlSi10Mg and Al6061 alloys needed to achieve “optimum” values for each performance characteristic. A process map was developed for each material by combining the optimized range of SLM process parameters for each characteristic to ensure good quality of the as-built parts. This study is also aimed at reducing the amount of post-processing needed according to the optimal processing window detected.

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