The impact of temperature changing on surface roughness of FFF process

Chaidas, Dimitrios; Kitsakis, Konstantinos; Kechagias, John; Maropoulos, Stergios

doi:10.1088/1757-899x/161/1/012033

Cited by 50 publications

(26 citation statements)

References 4 publications

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“…This open source 3D printer manufactured by Ultimaker Ltd. is based on the Replicating Rapid-prototyper technology and it has been awarded as the fastest and most accurate 3D printer in 2012. Some technical specifications of the 3D printer are [32,33] As it is mentioned above, the printing material used in this investigation is polylactic acid (PLA). PLA is a thermoplastic polyester material with good processing performance and acceptable mechanical properties [34,35].…”

Section: Workpiece Preperation 3d Printer and Printing Materialsmentioning

confidence: 99%

“…Next, dimensional deviation was derived, which is the difference between the nominal and the averaged measured values and represents the parts' dimensional accuracy. A micrometer with a range of 25-50 mm and 0.01 mm accuracy was utilized for the dimensional measurements [33]. The dimensional measurements for every part and the direction are presented in Table 3, while the dimensional calculations are tabulated in Table 4.…”

Section: Measurement Techniquesmentioning

confidence: 99%

“…The dimensional measurements for every part and the direction are presented in Table 3, while the dimensional calculations are tabulated in Table 4. In the case of surface roughness measurements, a Mitutoyo Surftest SJ-210 roughness tester was utilized with a "cut off length" of 0.8 mm, along Z axis direction [32]. The four surface texture parameters measured during this experiment are defined as follows [44]:…”

Section: Measurement Techniquesmentioning

confidence: 99%

“…To the best of authors' knowledge, the multi-objective optimization of the dimensional accuracy and surface roughness of FDM printed parts in terms of extraction temperature and wall thickness has not been addressed before. Two previous studies have been conducted regarding the dimensional accuracy and the surface roughness measurements of these FDM thin walled parts, in which no optimization or evaluation analysis was done (see [32,33]).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis

Aslani

Chaidas

Kechagias

et al. 2020

JMMP

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This paper investigates the quality performance of FDM 3D printed models with thin walls. The design of experiments method (DOE) was used and nine models of the same size were fabricated in a low-cost 3D printer using polylactic acid (PLA) material. Two limited studied parameters were considered (extraction temperature and wall thickness), each one having three levels. External X and Y dimensions were measured using a micrometer, as well as four surface roughness parameters (Ra, Rz, Rt, Rsm) with a surface tester. Two optimization techniques (the Taguchi approach and Grey relational analysis) were utilized along with statistical analysis to examine how the temperature and wall thickness affect the dimensional accuracy and the surface quality of the parts. The results showed that high extraction temperature and median wall thickness values optimize both dimensional accuracy and surface roughness, while temperature is the most important factor.

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Section: Workpiece Preperation 3d Printer and Printing Materialsmentioning

confidence: 99%

Section: Measurement Techniquesmentioning

confidence: 99%

Section: Measurement Techniquesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis

Aslani

Chaidas

Kechagias

et al. 2020

JMMP

View full text Add to dashboard Cite

show abstract

“…Plus 2 ® can be attributed to the heated platform. As the evaluation model is relatively thin, the presence of an additional heat source slows down the solidification process, which favors material flow and accommodation, thus reducing the average Ra value as reported by [36,37].…”

Section: Surface Roughnessmentioning

confidence: 99%

Selecting low-cost 3D printers using the AHP method: a case study

et al. 2019

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The purpose of this paper is to present a selection method based on analytic hierarchy process in the form of a case study, which benefits from quantitative data to assess the performance of low-cost 3D printers. The market of personal 3D printers has experienced a major boost in the last decade, with an apparently ever-increasing number of companies producing and selling machines. The huge variety of models available under $5000 has turned the selection of 3D printers into a complex task, often involving multiple questions. Many benchmarking parts have been proposed as a mean of comparing the performance of these machines in relation to geometric, mechanical and process aspects, with no consensus about the optimal model for every situation. Also, several decision-making methods mostly based on qualitative evaluation have been applied in order to rationalize the selection of such equipment. The evaluation metrics considered in the procedure were derived from a general goal, organized in a hierarchical structure and then compared according to the context of the research. A real application model, from an innovative project, was fabricated by three different machines and then evaluated regarding multiple criteria with distinct importance. The evaluation included surface roughness, dimensional and geometric accuracy, building time and material usage measurements. The case study shows a less subjective way to evaluate the performance of such machines, which can be easily implemented by the academic and 3D printing communities, considering different scenarios and even diverse technologies.

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Hybrid Material Extrusion Process Optimization for Printability and Adhesion in 3D‐Printed Electronics

Fu,

Salo,

Calvo Guzman

et al. 2024

Adv Eng Mater

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3D printing exhibits strong potential in electronics manufacturing for its quick prototyping and capability of manufacturing complex structures with a wide range of materials. However, thermoplastic polyurethane (TPU) has rarely been fabricated by 3d printing for electronics due to the limited understanding of its printability and the adhesion of the conductors on it. In this research, we investigate the printability of TPU using varying layer height and printing temperature in the Materials Extrusion (MEX) process, their impacts on the printability, and the adhesion of conductive trace on TPU. The printability is characterized by the surface roughness, stability of dimension and mass, and the adhesion is evaluated by a standard cross‐cutting method. In this research, 0.2 mm layer height and 220 °C printing temperature have consistently proven to be optimal configuration parameters for MEX printing of TPU. Larger layer height in TPU printing causes poorer printing quality (lower dimensional accuracy, more porous structure, rougher surface), lower ink‐TPU adhesion, and transforms the adhesive failure of ink against peeling to cohesive failure. Higher printing temperature causes less homogeneous structure and rougher surface with minor influence on the width and conductivity of ink on TPU, and no influence on the mechanism of ink failure against peeling.This article is protected by copyright. All rights reserved.

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The impact of temperature changing on surface roughness of FFF process

Cited by 50 publications

References 4 publications

Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis

Quality Performance Evaluation of Thin Walled PLA 3D Printed Parts Using the Taguchi Method and Grey Relational Analysis

Selecting low-cost 3D printers using the AHP method: a case study

Hybrid Material Extrusion Process Optimization for Printability and Adhesion in 3D‐Printed Electronics

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