Predictive modeling of geometric deviations of 3D printed products - A unified modeling approach for cylindrical and polygon shapes

Huang, Qiang; Nouri, Hadis; Xu, Kai; Chen, Yong; Sosina, Sobambo; Dasgupta, Tirthankar

doi:10.1109/coase.2014.6899299

Cited by 33 publications

(32 citation statements)

References 11 publications

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“…[14,15] and [8,9] For complete control of all local features around the perimeter of a AM built part, Huang et al [8] established a generic approach to model and predict part deviations and subsequently derived an optimal compensation plan to achieve dimensional accuracy. The essence of this new modeling approach is to transform in-plane (x-y plane) geometric errors into a functional profile defined on the polar coordinate system (PCS).…”

Section: Variables Observedmentioning

confidence: 99%

“…Huang et al [9] attempted to connect the model for cylindrical shape with the model for polygon shapes in a unified modeling framework. The proposed model contains a basis function for cy lindrical shape and a cookie-cutter basis function to carve out the polygon shape from the cylindrical shape.…”

Section: Variables Observedmentioning

confidence: 99%

“…In addition, individual models were fitted for each shape in Ref. [9], as opposed to a single integrated model. No compensation studies were provided to validate the proposed models.…”

Section: Variables Observedmentioning

confidence: 99%

“…Despite these promising features, dimensional accuracy control remains a major bottleneck for the application of 3D printing in direct manufacturing [6][7][8][9]. Shape deviations of AM built prod ucts can be attributed to multiple variation sources.…”

Section: Introductionmentioning

confidence: 99%

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Statistical Predictive Modeling and Compensation of Geometric Deviations of Three-Dimensional Printed Products

Huang

Nouri

et al. 2014

Journal of Manufacturing Science and Engineering

Self Cite

107

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Geometric fidelity of 3D printed products is critical for additive manufacturing (AM) to be a direct manufacturing technology. Shape deviations of AM built products can be attributed to multiple variation sources such as substrate geometry defect, disturbance in process variables, and material phase change. Three strategies have been reported to improve geometric quality in AM: (1) control process variables x based on the observed disturbance of process variables Ax, (2) control process variables x based on the observed product deviation Ay, and (3) control input product geometry y based on the observed product deviation Ay. This study adopts the third strategy which changes the computer-aided design (CAD) design by optimally compensating the product deviations. To accomplish the goal, a predictive model is desirable to forecast the quality of a wide class o f product shapes, particularly considering the vast library of AM built products with complex geometry. Built upon our previous optimal compensation study of cylindrical products, this work aims at a novel statistical predictive modeling and compensation approach to predict and improve the quality of both cylindrical and prismatic parts. Ex perimental investigation and validation of polyhedrons a indicates the promise of predict ing and compensating a wide class of products built through 3D printing technology.

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Section: Variables Observedmentioning

confidence: 99%

Section: Variables Observedmentioning

confidence: 99%

“…In addition, individual models were fitted for each shape in Ref. [9], as opposed to a single integrated model. No compensation studies were provided to validate the proposed models.…”

Section: Variables Observedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Statistical Predictive Modeling and Compensation of Geometric Deviations of Three-Dimensional Printed Products

Huang

Nouri

et al. 2014

Journal of Manufacturing Science and Engineering

Self Cite

107

View full text Add to dashboard Cite

show abstract

“…Tong et al (2003); Tong et al (2008) propose a parametric error model, which models the repeatable errors of stereo lithography appearance (SLA) machine and FDM machine with generic parametric error functions. Huang and his research team have been dedicated to developing a predictive model of geometric deviations that can learn from the deviation information obtained from a certain number of tested product shapes (Huang et al 2014a(Huang et al , b, 2015Kusiak et al 2008;Xu et al 2013). Geometric accuracy is one of the most important indicators of FDM product quality.…”

Section: Introductionmentioning

confidence: 99%

Profile monitoring based quality control method for fused deposition modeling process

Zhang

Hong

2018

J Intell Manuf

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In order to monitor the quality of parts in printing, the methodology to monitor the geometric quality of the printed parts in fused deposition modeling process is researched. A non-contact measurement method based on machine vision technology is adopted to obtain the precise complete geometric information. An image acquisition system is established to capture the image of each layer of the part in building and image processing technology is used to obtain the geometric profile information. With the above information, statistical process control method is applied to monitor the geometric quality of the parts during the printing process. Firstly, a border signature method is applied to transform complex geometry into a simple distance-angle function to get the profile deviation data. Secondly, monitoring of the profile deviation data based on profile monitoring method is studied and applied to achieve the goal of layer-to-layer monitoring. In the research, quantile-quantile plot method is used to transform the profile deviation point cloud data monitoring problem into a linear profile relationship monitoring problem and EWMA control charts are established to monitor the parameters of the linear relationship to detect shifts occurred in the Fused Deposition Modeling process. Finally, laboratory experiments are conducted to demonstrate the effectiveness of the proposed approach.

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Geometric Accuracy and Mechanical Behavior of PA6 Composite Curved Tubes Fabricated by Fused Filament Fabrication (FFF)

2022

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Herein, the effect of processing parameters including infill pattern and reinforcement type on the dimensional accuracy of products manufactured by the fused filament fabrication (FFF) process as well as the mechanical performance is studied. The reinforcements used to manufacture the PA6 composite are carbon, Kevlar, and glass fibers. The compression properties of the stated composites are compared. The results show that the rectangular fill pattern is less deformed compared with triangular, hexagonal, and solid ones. However, the compression strength is decreased by changing the infill pattern from the solid infill to hexagonal, triangular, and rectangular. Although there is no significant difference in terms of compression behavior, the printed PA6 reinforced with carbon fiber which is deformed outward contrary to Kevlar and glass fibers, which are deformed inward. Finally, the results confirm that the selection of the appropriate types of reinforcements and infill patterns among the several available types during the printing process is effective in improving the mechanical properties and also in providing better geometrical quality of the surfaces and the consequent dimensional precision improvement of the parts printed by the FFF process.

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Predictive modeling of geometric deviations of 3D printed products - A unified modeling approach for cylindrical and polygon shapes

Cited by 33 publications

References 11 publications

Statistical Predictive Modeling and Compensation of Geometric Deviations of Three-Dimensional Printed Products

Statistical Predictive Modeling and Compensation of Geometric Deviations of Three-Dimensional Printed Products

Profile monitoring based quality control method for fused deposition modeling process

Geometric Accuracy and Mechanical Behavior of PA6 Composite Curved Tubes Fabricated by Fused Filament Fabrication (FFF)

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