Research graph
References from Machine-Learning-Based Analysis of Printing-Parameter Effects on Surface Roughness in FDM-Printed ULTEM 1010 Parts. Local targets link to admitted publications; unresolved targets remain external evidence.
Anisotropic material properties of fused deposition modeling ABS
10.1108/13552540210441166 · 2002 · External reference
Generalized models for unidirectional anisotropic properties of 3D printed polymers
10.1108/rpj-03-2019-0083 · 2020 · External reference
Isotropic and anisotropic elasticity and yielding of 3D printed material
10.1016/j.compositesb.2016.06.009 · 2016 · External reference
10.3390/app151810001
10.3390/app151810001 · External reference
Surface roughness modeling of material extrusion PLA flat surfaces
10.1155/2023/8844626 · 2023 · External reference
Investigation of FDM process parameters and their interactions on surface roughness of PLA 3D printed parts
10.1088/1742-6596/3058/1/012017 · 2025 · External reference
Investigation of contour-related parameters’ effects on anisotropic mechanical properties and surface roughness of FDM-printed parts
10.1007/s00170-025-15128-3 · 2025 · External reference
3D printing of glass fiber reinforced acrylonitrile butadiene styrene and investigation of tensile, flexural, warpage and roughness properties
10.1002/pc.26937 · 2022 · External reference
Surface roughness and printing time minimization in 3D printed aramid fiber reinforced polyamide parts through Taguchi-CoCoSo-Machine learning techniques
10.1007/s11665-025-11288-1 · 2025 · External reference
A review of machine learning (ML) and explainable artificial intelligence (XAI) methods in additive manufacturing (3D Printing)
10.1016/j.mtcomm.2024.110294 · 2024 · External reference
Quality prediction of fused deposition molding parts based on improved deep belief network
10.1155/2021/8100371 · 2021 · External reference
Multi objective optimization of FDM 3D printing parameters set via design of experiments and machine learning algorithms
10.1038/s41598-025-01016-z · 2025 · External reference
10.3390/polym17152012
10.3390/polym17152012 · External reference
FDM manufactured auxetic structures: An investigation of mechanical properties using machine learning techniques
10.1016/j.ijsolstr.2023.112126 · 2023 · External reference
A machine learning–integrated framework for mechanical property prediction of FDM–printed PLA
10.1007/s00170-025-16232-0 · 2025 · External reference
Machine Learning Prediction of Raster Angle Effects on Mechanical Properties of Extrusion-Based Additively Manufactured Conductive Thermoplastic Polyurethane Composites
10.1002/mame.202500248 · 2026 · External reference
Predicting mechanical properties of FDM-produced parts using machine learning approaches
10.1002/app.56899 · 2025 · External reference
Use of machine learning algorithms for surface roughness prediction of printed parts in polyvinyl butyral via fused deposition modeling
10.1007/s00170-021-07300-2 · 2021 · External reference
10.3390/polym12040840
10.3390/polym12040840 · External reference
Evaluating machine learning methods for predicting surface roughness of FDM printed parts using PLA plus material
10.1007/s12008-024-02215-0 · 2025 · External reference
10.3390/pr11061820
10.3390/pr11061820 · External reference
Research and application of machine learning for additive manufacturing
2022 · External reference
A comprehensive review on smart manufacturing using machine learning applicable to fused deposition modeling
10.1016/j.rineng.2025.104941 · 2025 · External reference
Surface roughness prediction of FFF-fabricated workpieces by artificial neural network and Box–Behnken method
10.1051/ijmqe/2021014 · 2021 · External reference
Optimization and prediction of mechanical properties of TPU-Based wrist hand orthosis using Bayesian and machine learning models
10.1016/j.measurement.2025.117405 · 2025 · External reference
Taguchi-ANN Hybrid Approach for Evaluating Unsupported Overhang Structures in FDM-Printed Polymers
10.1002/pol.20250752 · 2025 · External reference
Machine learning-based prediction and optimization of surface roughness in FDM-printed PLA using ANN and box-behnken design
10.1177/02670836251370811 · 2025 · External reference
Surface Roughness Prediction of Laser-Polished 3D-Printed Polylactic Acid Parts: A Combined Experimental and Machine Learning Approach
2025 · External reference
ANN modelling of surface roughness of FDM parts considering the effect of hidden layers, neurons, and process parameters
2024 · External reference
Experimental analysis and a novel stepwise nonlinear hybrid ANN-based machine learning approach for optimizing the mechanical and surface performance of 3D-printed PLA
10.1016/j.measurement.2025.119648 · 2025 · External reference
10.1016/j.matpr.2023.03.378
10.1016/j.matpr.2023.03.378 · External reference
10.3390/polym17111528
10.3390/polym17111528 · External reference
Sustainable additive manufacturing with FDM: Taguchi-based parameter optimization and AI-driven prediction of mechanical and environmental metrics
10.1177/08927057261415795 · 2026 · External reference
Analyzing the impact of process parameters on surface roughness and mechanical properties in FDM 3D printing using machine learning
10.1007/s12008-025-02313-7 · 2025 · External reference
10.1080/10589759.2025.2591853
10.1080/10589759.2025.2591853 · External reference
Novel coupled genetic algorithm–machine learning approach for predicting surface roughness in fused deposition modeling of polylactic acid specimens
10.1007/s11665-023-08379-2 · 2024 · External reference
Nonparametric bayesian framework for material and process optimization with nanocomposite fused filament fabrication
2022 · External reference
Optimization of print parameters for batch and continuous manufacturing of three-dimensional (3D) printed dosage forms using artificial intelligence and machine learning
10.1007/s13346-025-02006-4 · 2026 · External reference
10.3390/app131911027
10.3390/app131911027 · External reference
Effect of machining parameters on surface roughness for compacted graphite cast iron by analyzing covariance function of Gaussian process regression
10.1016/j.measurement.2020.107578 · 2020 · External reference
Empirical study and machine learning prediction of tensile strength in 3D printed eco-friendly polylactic acid
2026 · External reference
Active learning for prediction of tensile properties for material extrusion additive manufacturing
10.1038/s41598-023-38527-6 · 2023 · External reference
Predicting the dynamic tensile response of FDM materials using machine learning
10.1007/s42452-025-08049-z · 2026 · External reference
Predicting flexural properties of 3D-printed composites: A small dataset analysis using multiple machine learning models
10.1016/j.mtcomm.2024.111135 · 2025 · External reference
Critical quality indicators of high-performance polyetherimide (ULTEM) over the MEX 3D printing key generic control parameters: Prospects for personalized equipment in the defense industry
10.1016/j.dt.2024.08.001 · 2025 · External reference
A design framework for multi-thermal optimization of ULTEM 1010 using open-source FDM: Unlocking its additive manufacturing potential
10.1016/j.matdes.2025.114407 · 2025 · External reference
Interpreting the effect of critical control settings on the quality metrics of thermoplastic polyimide in extrusion based additive manufacturing
10.1007/s00170-026-17498-8 · 2026 · External reference
Characterisation of high-performance polymer parts produced by low-pressure additive manufacturing
10.1007/s12567-025-00632-9 · 2026 · External reference
10.3390/polym15030561
10.3390/polym15030561 · External reference
Unresolved reference
External reference
Parametric study on tensile and flexural properties of ULTEM 1010 specimens fabricated via FDM
10.1108/rpj-10-2019-0274 · 2021 · External reference
Unresolved reference
External reference
Advances in interlayer bonding in fused deposition modelling: A comprehensive review
10.1080/17452759.2025.2522951 · 2025 · External reference
Rheology, crystallinity, and mechanical investigation of interlayer adhesion strength by thermal annealing of polyetherimide (PEI/ULTEM 1010) parts produced by 3D printing
10.1007/s11665-022-07049-z · 2022 · External reference
Optimization of a combined thermal annealing and isostatic pressing process for mechanical and surface enhancement of Ultem FDM parts using Doehlert experimental designs
10.1016/j.jmapro.2022.12.027 · 2023 · External reference
10.3390/jmmp8060258
10.3390/jmmp8060258 · External reference
Effect of in situ thermal treatment on interlayer adhesion of 3D printed polyetherimide (PEI) parts produced by fused deposition modeling (FDM)
10.1016/j.mtcomm.2024.108588 · 2024 · External reference
Investigating the effect of printing conditions and annealing on the porosity and tensile behavior of 3D-printed polyetherimide material in Z-direction
10.1002/app.53353 · 2023 · External reference
Investigating the effect of printing conditions and annealing on the porosity and tensile behavior of 3D-printed polyetherimide material in Z-direction
10.1002/app.53353 · ExternalCitation · doi-reference
Predicting mechanical properties of FDM-produced parts using machine learning approaches
10.1002/app.56899 · ExternalCitation · doi-reference
Machine Learning Prediction of Raster Angle Effects on Mechanical Properties of Extrusion-Based Additively Manufactured Conductive Thermoplastic Polyurethane Composites
10.1002/mame.202500248 · ExternalCitation · doi-reference
3D printing of glass fiber reinforced acrylonitrile butadiene styrene and investigation of tensile, flexural, warpage and roughness properties
10.1002/pc.26937 · ExternalCitation · doi-reference
Taguchi-ANN Hybrid Approach for Evaluating Unsupported Overhang Structures in FDM-Printed Polymers
10.1002/pol.20250752 · ExternalCitation · doi-reference
Use of machine learning algorithms for surface roughness prediction of printed parts in polyvinyl butyral via fused deposition modeling
10.1007/s00170-021-07300-2 · ExternalCitation · doi-reference
Investigation of contour-related parameters’ effects on anisotropic mechanical properties and surface roughness of FDM-printed parts
10.1007/s00170-025-15128-3 · ExternalCitation · doi-reference
A machine learning–integrated framework for mechanical property prediction of FDM–printed PLA
10.1007/s00170-025-16232-0 · ExternalCitation · doi-reference
Interpreting the effect of critical control settings on the quality metrics of thermoplastic polyimide in extrusion based additive manufacturing
10.1007/s00170-026-17498-8 · ExternalCitation · doi-reference
Rheology, crystallinity, and mechanical investigation of interlayer adhesion strength by thermal annealing of polyetherimide (PEI/ULTEM 1010) parts produced by 3D printing
10.1007/s11665-022-07049-z · ExternalCitation · doi-reference
Novel coupled genetic algorithm–machine learning approach for predicting surface roughness in fused deposition modeling of polylactic acid specimens
10.1007/s11665-023-08379-2 · ExternalCitation · doi-reference
Surface roughness and printing time minimization in 3D printed aramid fiber reinforced polyamide parts through Taguchi-CoCoSo-Machine learning techniques
10.1007/s11665-025-11288-1 · ExternalCitation · doi-reference
Evaluating machine learning methods for predicting surface roughness of FDM printed parts using PLA plus material
10.1007/s12008-024-02215-0 · ExternalCitation · doi-reference
Analyzing the impact of process parameters on surface roughness and mechanical properties in FDM 3D printing using machine learning
10.1007/s12008-025-02313-7 · ExternalCitation · doi-reference
Characterisation of high-performance polymer parts produced by low-pressure additive manufacturing
10.1007/s12567-025-00632-9 · ExternalCitation · doi-reference
Optimization of print parameters for batch and continuous manufacturing of three-dimensional (3D) printed dosage forms using artificial intelligence and machine learning
10.1007/s13346-025-02006-4 · ExternalCitation · doi-reference
Predicting the dynamic tensile response of FDM materials using machine learning
10.1007/s42452-025-08049-z · ExternalCitation · doi-reference
Isotropic and anisotropic elasticity and yielding of 3D printed material
10.1016/j.compositesb.2016.06.009 · ExternalCitation · doi-reference
Critical quality indicators of high-performance polyetherimide (ULTEM) over the MEX 3D printing key generic control parameters: Prospects for personalized equipment in the defense industry
10.1016/j.dt.2024.08.001 · ExternalCitation · doi-reference
FDM manufactured auxetic structures: An investigation of mechanical properties using machine learning techniques
10.1016/j.ijsolstr.2023.112126 · ExternalCitation · doi-reference
Optimization of a combined thermal annealing and isostatic pressing process for mechanical and surface enhancement of Ultem FDM parts using Doehlert experimental designs
10.1016/j.jmapro.2022.12.027 · ExternalCitation · doi-reference
A design framework for multi-thermal optimization of ULTEM 1010 using open-source FDM: Unlocking its additive manufacturing potential
10.1016/j.matdes.2025.114407 · ExternalCitation · doi-reference
10.1016/j.matpr.2023.03.378
10.1016/j.matpr.2023.03.378 · ExternalCitation · doi-reference
Effect of machining parameters on surface roughness for compacted graphite cast iron by analyzing covariance function of Gaussian process regression
10.1016/j.measurement.2020.107578 · ExternalCitation · doi-reference
Optimization and prediction of mechanical properties of TPU-Based wrist hand orthosis using Bayesian and machine learning models
10.1016/j.measurement.2025.117405 · ExternalCitation · doi-reference
Experimental analysis and a novel stepwise nonlinear hybrid ANN-based machine learning approach for optimizing the mechanical and surface performance of 3D-printed PLA
10.1016/j.measurement.2025.119648 · ExternalCitation · doi-reference
Effect of in situ thermal treatment on interlayer adhesion of 3D printed polyetherimide (PEI) parts produced by fused deposition modeling (FDM)
10.1016/j.mtcomm.2024.108588 · ExternalCitation · doi-reference
A review of machine learning (ML) and explainable artificial intelligence (XAI) methods in additive manufacturing (3D Printing)
10.1016/j.mtcomm.2024.110294 · ExternalCitation · doi-reference
Predicting flexural properties of 3D-printed composites: A small dataset analysis using multiple machine learning models
10.1016/j.mtcomm.2024.111135 · ExternalCitation · doi-reference
A comprehensive review on smart manufacturing using machine learning applicable to fused deposition modeling
10.1016/j.rineng.2025.104941 · ExternalCitation · doi-reference
Active learning for prediction of tensile properties for material extrusion additive manufacturing
10.1038/s41598-023-38527-6 · ExternalCitation · doi-reference
Multi objective optimization of FDM 3D printing parameters set via design of experiments and machine learning algorithms
10.1038/s41598-025-01016-z · ExternalCitation · doi-reference
Surface roughness prediction of FFF-fabricated workpieces by artificial neural network and Box–Behnken method
10.1051/ijmqe/2021014 · ExternalCitation · doi-reference
10.1080/10589759.2025.2591853
10.1080/10589759.2025.2591853 · ExternalCitation · doi-reference
Advances in interlayer bonding in fused deposition modelling: A comprehensive review
10.1080/17452759.2025.2522951 · ExternalCitation · doi-reference
Investigation of FDM process parameters and their interactions on surface roughness of PLA 3D printed parts
10.1088/1742-6596/3058/1/012017 · ExternalCitation · doi-reference
Anisotropic material properties of fused deposition modeling ABS
10.1108/13552540210441166 · ExternalCitation · doi-reference
Generalized models for unidirectional anisotropic properties of 3D printed polymers
10.1108/rpj-03-2019-0083 · ExternalCitation · doi-reference
Parametric study on tensile and flexural properties of ULTEM 1010 specimens fabricated via FDM
10.1108/rpj-10-2019-0274 · ExternalCitation · doi-reference
Quality prediction of fused deposition molding parts based on improved deep belief network
10.1155/2021/8100371 · ExternalCitation · doi-reference
Surface roughness modeling of material extrusion PLA flat surfaces
10.1155/2023/8844626 · ExternalCitation · doi-reference
Machine learning-based prediction and optimization of surface roughness in FDM-printed PLA using ANN and box-behnken design
10.1177/02670836251370811 · ExternalCitation · doi-reference
Sustainable additive manufacturing with FDM: Taguchi-based parameter optimization and AI-driven prediction of mechanical and environmental metrics
10.1177/08927057261415795 · ExternalCitation · doi-reference
10.3390/app131911027
10.3390/app131911027 · ExternalCitation · doi-reference
10.3390/app151810001
10.3390/app151810001 · ExternalCitation · doi-reference
10.3390/jmmp8060258
10.3390/jmmp8060258 · ExternalCitation · doi-reference
10.3390/polym12040840
10.3390/polym12040840 · ExternalCitation · doi-reference
10.3390/polym15030561
10.3390/polym15030561 · ExternalCitation · doi-reference
10.3390/polym17111528
10.3390/polym17111528 · ExternalCitation · doi-reference
10.3390/polym17152012
10.3390/polym17152012 · ExternalCitation · doi-reference
10.3390/pr11061820
10.3390/pr11061820 · ExternalCitation · doi-reference
