A Study of Build Edge Profile for Prediction of Surface Roughness in Fused Deposition Modeling

2016 ◽  
Vol 138 (6) ◽  
Author(s):  
Mohammad Taufik ◽  
Prashant K. Jain
Keyword(s):  
Surface Roughness ◽  
Fused Deposition Modeling ◽  
Prediction Errors ◽  
Empirical Methods ◽  
Fused Deposition ◽  
Predictive Error ◽  
Layer Deposition ◽  
Edge Profile ◽  
Roughness Prediction ◽  
Deposition Modeling

Surface roughness prediction studies in fused deposition modeling (FDM) process are usually based on a perimeter profile of each deposited layer. This study categorizes three types of build edge profile composed of perimeter, raster, and combination of both layer deposition patterns, which have been considered to reduce the predictive error of roughness models. Furthermore, an innovative approach based on combination of theoretical and empirical methods is used to analyze and predict the randomness in the geometry of build edge profiles. The same methodology is used to model the roughness profile and surface roughness behaviors. The proposed models have been tested for robustness against varying build orientations and with data available in the existing literature. The robustness of the proposed models is compared with the existing models. The results clearly demonstrate that the proposed models are very useful in reducing prediction errors.

Influence of Part Orientation on the Surface Roughness in the Process of Fused Deposition Modeling

2021 ◽  
Vol 896 ◽  
pp. 29-37
Author(s):  
Ján Milde ◽  
František Jurina ◽  
Jozef Peterka ◽  
Patrik Dobrovszký ◽  
Jakub Hrbál ◽  
...  
Keyword(s):  
Surface Roughness ◽  
3D Printing ◽  
Fused Deposition Modeling ◽  
Orientation Angle ◽  
Acrylonitrile Butadiene Styrene ◽  
Lower Surface ◽  
Geometrical Model ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Part Orientation

The article focused on the influence of part orientation on the surface roughness of cuboid parts during the process of fabricating by FDM technology. The components, in this case, is simple cuboid part with the dimensions 15 mm x 15mm x 30 mm. A geometrical model is defined that considers the shape of the material filaments after deposition, to define a theoretical roughness profile, for a certain print orientation angle. Five different print orientations in the X-axis of the cuboid part were set: 0°, 30°, 45°, 60°, and 90°. According to previous research in the field of FDM technology by the author, the internal structure (infill) was set at the value of 70%. The method of 3D printing was the Fused Deposition Modeling (FDM) and the material used in this research was thermoplastic ABS (Acrylonitrile butadiene styrene). For each setting, there were five specimens (twenty five prints in total). Prints were fabricated on a Zortrax M200 3D printer. After the 3D printing, the surface “A” was investigated by portable surface roughness tester Mitutoyo SJ-210. Surface roughness in the article is shown in the form of graphs (Fig.7). Results show increase in part roughness with increasing degree of part orientation. When the direction of applied layers on the measured surface was horizontal, significant improvement in surface roughness was observed. Findings in this paper can be taken into consideration when designing parts, as they can contribute in achieving lower surface roughness values.

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.

scholarly journals Improvement of Surface Roughness and Hydrophobicity in PETG Parts Manufactured via Fused Deposition Modeling (FDM): An Application in 3D Printed Self–Cleaning Parts

Materials ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2499 ◽  
Author(s):  
Juan M. Barrios ◽  
Pablo E. Romero
Keyword(s):  
Surface Roughness ◽  
Contact Angle ◽  
Flow Rate ◽  
Fused Deposition Modeling ◽  
Light Emitting Diode ◽  
P Value ◽  
Sliding Angle ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Self Cleaning

The fused deposition modeling (FDM) technique is used today by companies engaged in the fabrication of traffic signs for the manufacture of light-emitting diode LED spotlights. In this sector, the surface properties of the elements used (surface finish, hydrophobic features) are decisive because surfaces that retain little dirt and favor self–cleaning behavior are needed. A design of experiments (L27) with five factors and three levels has been carried out. The factors studied were: Layer height (LH), print temperature (T), print speed (PS), print acceleration (PA), and flow rate (F). Polyethylene terephthalate glycol (PETG) specimens of 25.0 × 25.0 × 2.4 mm have been printed and, in each of them, the surface roughness (Ra,0, Ra,90), sliding angle (SA0, SA90), and contact angle (CA0, CA90) in both perpendicular directions have been measured. Taguchi and ANOVA analysis shows that the most influential variables in this case are printing acceleration for Ra, 0 (p–value = 0.052) and for SA0 (p–value = 0.051) and flow rate for Ra, 90 (p–value = 0.001) and for SA90 (p–value = 0.012). Although the ANOVA results for the contact angle are not significant, specimen 8 (PA = 1500 mm/s2 and flow rate F = 110%) and specimen 10 (PA =1500 mm/s2 and F = 100%) have reached contact angle values above or near the limit value for hydrophobia, respectively.

Improvement of Surface Roughness on ABS 400 Polymer Using Design of Experiments (DOE)

2007 ◽  
Vol 561-565 ◽  
pp. 2389-2392 ◽  
Author(s):  
Daniel Horvath ◽  
Rafiq Noorani ◽  
Mel Mendelson
Keyword(s):  
Surface Roughness ◽  
Fused Deposition Modeling ◽  
Factorial Experiment ◽  
Full Factorial Experiment ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Full Factorial ◽  
Model Temperature ◽  
Three Factor ◽  
Significant Factors

The objective of this research was to find the best combination of factor levels that minimized the surface roughness of prototyped samples from Fused Deposition Modeling (FDM). Two sets of experiments were conducted for that purpose; a two-level three-factor full factorial experiment and a three-level two-factor full factorial experiment. The parameters chosen for this research were model temperature, layer thickness and part fill style. The results obtained from both experiments were compared and analyzed in order to determine the best combination of factors that minimized the surface roughness of the specimens. The significant factors, their interactions and the optimum setting are presented in this paper

A review of melt extrusion additive manufacturing processes: II. Materials, dimensional accuracy, and surface roughness

2015 ◽  
Vol 21 (3) ◽  
pp. 250-261 ◽  
Author(s):  
Brian N. Turner ◽  
Scott A Gold
Keyword(s):  
Surface Roughness ◽  
Additive Manufacturing ◽  
Product Design ◽  
Fused Deposition Modeling ◽  
Dimensional Accuracy ◽  
Design Parameters ◽  
Content Type ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Am Processes

Purpose – The purpose of this paper is to critically review the literature related to dimensional accuracy and surface roughness for fused deposition modeling and similar extrusion-based additive manufacturing or rapid prototyping processes. Design/methodology/approach – A systematic review of the literature was carried out by focusing on the relationship between process and product design parameters and the dimensional and surface properties of finished parts. Methods for evaluating these performance parameters are also reviewed. Findings – Fused deposition modeling® and related processes are the most widely used polymer rapid prototyping processes. For many applications, resolution, dimensional accuracy and surface roughness are among the most important properties in final parts. The influence of feedstock properties and system design on dimensional accuracy and resolution is reviewed. Thermal warping and shrinkage are often major sources of dimensional error in finished parts. This phenomenon is explored along with various approaches for evaluating dimensional accuracy. Product design parameters, in particular, slice height, strongly impact surface roughness. A geometric model for surface roughness is also reviewed. Originality/value – This represents the first review of extrusion AM processes focusing on dimensional accuracy and surface roughness. Understanding and improving relationships between materials, design parameters and the ultimate properties of finished parts will be key to improving extrusion AM processes and expanding their applications.

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