Modeling of Linear Shrinkage in PLA Parts Fabricated by 3D Printing Using TOPSIS Method

Mago, Jonty; Kumar, Ravi; Agrawal, Raj; Singh, Anoop; Srivastava, Vineet

doi:10.1007/978-981-32-9433-2_23

Cited by 16 publications

(10 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This method has a long history and nowadays has numerous applications in industrial and manufacturing (Ref 49,50); it is specifically used in combination with finite element models. ( Ref 51,52). In general, in manufacturing and modeling uncertainty, the RSM is a good solution.…”

Section: Response Surface Methodsmentioning

confidence: 99%

Statistical and Experimental Analysis of Process Parameters of 3D Nylon Printed Parts by Fused Deposition Modeling: Response Surface Modeling and Optimization

Moradi

Aminzadeh

Rahmatabadi

et al. 2021

J. of Materi Eng and Perform

View full text Add to dashboard Cite

In the current study, the additive manufacturing of nylon by fused deposition modeling is conducted based on statistical analysis. Besides, the aim of this study is the influence of process parameters, namely layer thickness (0.15 mm-0.35 mm), infill percentage (15-55%), and the number of contours (2-6) on the maximum failure load, parts weight, elongation at break, and build time. The experiment approach was used to optimize process parameters based on the statistical evaluates to reach the best objective function. The minimum value of build time and maximize of the failure load were considered as objective functions. The response surface method is regarded as an optimization process parameter, and optimum conditions were studied by experimental research to evaluate efficiency. Based on the results, the layer thickness is the significant primary variable for all responses. The experimental evaluation showed that the maximum values of failure load and elongation were obtained by changing the layer thickness from the lowest to the highest. By reduction in layer thickness at the same printing speed, the cooling rate increases, which results in greater strength and less elongation. As a result, it could be concluded that by increasing the number of contour layers from 2 to 6, the maximum failure force increased 42%. Increasing the contours due to the similar effect to increasing the infill density, increases the failure force and production time, which is also confirmed by the ANOVA.

show abstract

Section: Response Surface Methodsmentioning

confidence: 99%

Statistical and Experimental Analysis of Process Parameters of 3D Nylon Printed Parts by Fused Deposition Modeling: Response Surface Modeling and Optimization

Moradi

Aminzadeh

Rahmatabadi

et al. 2021

J. of Materi Eng and Perform

View full text Add to dashboard Cite

show abstract

“…This scheme is precious for getting the optimized set of parameters. [34][35][36] The experimental trials were decided based on the number of parameters and their different levels. A total of 27 experiments (nine order runs with three repetitions) were performed.…”

Section: Experimental Setup and Drilling Proceduresmentioning

confidence: 99%

Prediction of surface roughness and cutting force induced during rotary ultrasonic bone drilling via statistical and machine learning algorithms

Agarwal

Gupta

Singh

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

The ultrasonic-assisted drilling of bone is gaining significant attention in orthopedic research and clinical applications due to the advantage of reducing thermal necrosis, cutting force, and microcracks. Mechanical and surface morphological damage due to cutting force and surface roughness rise during bone drilling may result in implant failure during osteosynthesis. It is difficult to predict and measure cutting force and surface irregularities during real-time medical orthopedic surgery. Therefore, the present work uses the application of different machine learning models to predict cutting force and surface roughness induced during bone drilling. The predictive results of machine learning models were compared with statistical analysis. During the study, rotary ultrasonic drilling is performed on the pig femur bone. The surface roughness and cutting forces are monitored using a surface roughness tester and a dynamometer respectively. Predictive models were developed by drilling parameters such as spindle rotational speed, abrasive girt size, and feed rate. Various machine learning algorithms such as ridge regression, lasso regression, support vector regression, multi-linear regression, and artificial neural networks were leveraged and compared at different error metrics to provide a robust predictive model. It was observed that ridge regression has the least error metrics compared to other machine learning algorithms during surface roughness prediction. Moreover, the most accurate model for predicting cutting force was support vector regression. The error metrics for statistical analysis were comparatively higher than the machine learning algorithms. Therefore, machine-learning algorithms are preferable for adequate prediction of surface roughness and cutting force induced during bone drilling compared to statistical analysis.

show abstract

“…It is relevant to note that in 3D printed Polylactic Acid (PLA) parts, the shrinkage decreases with an increase in layer height and print speed while it increases with print length [157], which could be relevant in the case of cementitious mixtures as well. Also, in metal fused filament fabrication (FFF), shrinkage is reported to be independent of the infill percentage [158] while fused deposition modeling (FDM) of PLA parts using viscoelastic models and numerical modeling have been used to develop interior structures (infills) that compensate for the overall shrinkage of the otherwise solid print.…”

Section: Materials Curing and Dryingmentioning

confidence: 99%

From analytical methods to numerical simulations: A process engineering toolbox for 3D concrete printing

Perrot

Alexandre

Nerella

et al. 2021

Cement and Concrete Composites

View full text Add to dashboard Cite

Modeling of Linear Shrinkage in PLA Parts Fabricated by 3D Printing Using TOPSIS Method

Cited by 16 publications

References 4 publications

Statistical and Experimental Analysis of Process Parameters of 3D Nylon Printed Parts by Fused Deposition Modeling: Response Surface Modeling and Optimization

Statistical and Experimental Analysis of Process Parameters of 3D Nylon Printed Parts by Fused Deposition Modeling: Response Surface Modeling and Optimization

Prediction of surface roughness and cutting force induced during rotary ultrasonic bone drilling via statistical and machine learning algorithms

From analytical methods to numerical simulations: A process engineering toolbox for 3D concrete printing

Contact Info

Product

Resources

About