scholarly journals Surface Quality Enhancement of Fused Deposition Modeling (FDM) Printed Samples Based on the Selection of Critical Printing Parameters

Materials ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 1382 ◽  
Author(s):  
Mercedes Pérez ◽  
Gustavo Medina-Sánchez ◽  
Alberto García-Collado ◽  
Munish Gupta ◽  
Diego Carou
Keyword(s):  
Surface Roughness ◽  
Additive Manufacturing ◽  
Surface Quality ◽  
Fused Deposition Modeling ◽  
Correlation Coefficients ◽  
Fused Deposition ◽  
Kendall’S Τ ◽  
Deposition Modeling ◽  
Printing Parameters ◽  
Selection Of

The present paper shows an experimental study on additive manufacturing for obtaining samples of polylactic acid (PLA). The process used for manufacturing these samples was fused deposition modeling (FDM). Little attention to the surface quality obtained in additive manufacturing processes has been paid by the research community. So, this paper aims at filling this gap. The goal of the study is the recognition of critical factors in FDM processes for reducing surface roughness. Two different types of experiments were carried out to analyze five printing parameters. The results were analyzed by means of Analysis of Variance, graphical methods, and non-parametric tests using Spearman’s ρ and Kendall’s τ correlation coefficients. The results showed how layer height and wall thickness are the most important factors for controlling surface roughness, while printing path, printing speed, and temperature showed no clear influence on surface roughness.

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.

scholarly journals Automated Testing and Characterization of Additive Manufacturing (ATCAM)

2021 ◽  
Author(s):  
Arash Alex Mazhari ◽  
Randall Ticknor ◽  
Sean Swei ◽  
Stanley Krzesniak ◽  
Mircea Teodorescu
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Cell System ◽  
Automated Testing ◽  
Fused Deposition ◽  
Deposition Modeling ◽  
Machine Calibration

AbstractThe sensitivity of additive manufacturing (AM) to the variability of feedstock quality, machine calibration, and accuracy drives the need for frequent characterization of fabricated objects for a robust material process. The constant testing is fiscally and logistically intensive, often requiring coupons that are manufactured and tested in independent facilities. As a step toward integrating testing and characterization into the AM process while reducing cost, we propose the automated testing and characterization of AM (ATCAM). ATCAM is configured for fused deposition modeling (FDM) and introduces the concept of dynamic coupons to generate large quantities of basic AM samples. An in situ actuator is printed on the build surface to deploy coupons through impact, which is sensed by a load cell system utilizing machine learning (ML) to correlate AM data. We test ATCAM’s ability to distinguish the quality of three PLA feedstock at differing price points by generating and comparing 3000 dynamic coupons in 10 repetitions of 100 coupon cycles per material. ATCAM correlated the quality of each feedstock and visualized fatigue of in situ actuators over each testing cycle. Three ML algorithms were then compared, with Gradient Boost regression demonstrating a 71% correlation of dynamic coupons to their parent feedstock and provided confidence for the quality of AM data ATCAM generates.

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.

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