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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Prediction of tensile strength in fused deposition modeling process using artificial neural network and fuzzy logic
Amanuel Diriba Tura, Hirpa G. Lemu, Hana Beyene Mamo, et al.
Progress in Additive Manufacturing (2022) Vol. 8, Iss. 3, pp. 529-539
Closed Access | Times Cited: 17

Showing 17 citing articles:

Influences of printing parameters on mechanical properties of recycled PET and PETG using fused granular fabrication technique
Phan Quoc Khang Nguyen, Jojibabu Panta, Tosin Famakinwa, et al.
Polymer Testing (2024) Vol. 132, pp. 108390-108390
Open Access | Times Cited: 16
Analysis of printing variables and material properties in fused deposition modeling for enhanced 3D printed parts
D. Kara Ali, Abass Enzi, Abdullah F. Huayier
AIP conference proceedings (2025) Vol. 3224, pp. 040049-040049
Closed Access | Times Cited: 1
Influence of FDM process parameters on tensile strength of parts printed by PLA material
Vishwjeet Ambade, S. W. Rajurkar, G. K. Awari, et al.
International Journal on Interactive Design and Manufacturing (IJIDeM) (2023)
Closed Access | Times Cited: 16
Machine learning-assisted prediction modeling for anisotropic flexural strength variations in fused filament fabrication of graphene reinforced poly-lactic acid composites
Tapish Raj, Amrit Tiwary, Akash Jain, et al.
Progress in Additive Manufacturing (2024)
Closed Access | Times Cited: 4
A Review of AI for optimization of 3D Printing of Sustainable Polymers and Composites
Malik Hassan, Manjusri Misra, Graham W. Taylor, et al.
Composites Part C Open Access (2024), pp. 100513-100513
Open Access | Times Cited: 4
Application of Soft Computing Techniques in the Optimization of 3D-Printed Piezoresistive Sensors
Milad Razbin, Mostafa Vahdani, S.A. Moshizi, et al.
Sensors and Actuators A Physical (2025), pp. 116277-116277
Closed Access
Optimization and prediction of mechanical properties of TPU-Based wrist hand orthosis using Bayesian and machine learning models
Kaplan Kaplan, Osman Ülkir, Fatma KUNCAN
Measurement (2025), pp. 117405-117405
Closed Access
Artificial Neural Network Performance Modeling and Evaluation of Additive Manufacturing 3D Printed Parts
Sivarao Subramonian, K. Kadirgama, Abdulkareem Sh. Mahdi Al‐Obaidi, et al.
Engineering Technology & Applied Science Research (2023) Vol. 13, Iss. 5, pp. 11677-11684
Open Access | Times Cited: 11
Evaluation on Material Anisotropy of Acrylonitrile Butadiene Styrene Printed via Fused Deposition Modelling
Nima Zohdi, Phan Quoc Khang Nguyen, Chunhui Yang
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 1870-1870
Open Access | Times Cited: 3
Predicting tensile strength of material extrusion parts during the pre-process using neural networks
Carsten Schmidt, Florian Berchtold, Rainer Griesbaum, et al.
The International Journal of Advanced Manufacturing Technology (2023) Vol. 128, Iss. 11-12, pp. 5129-5138
Open Access | Times Cited: 5
A new strategy for manufacturing, modeling, and optimization of 3D printed polylactide based on multiple nonlinear neuro regression analysis and stochastic optimization methods
Melih Savran, Levent Aydın, Asil Ayaz, et al.
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering (2024)
Closed Access | Times Cited: 1
An artificial neural network-based predictive model for tensile behavior estimation under uncertainty for fused deposition modeling
Sinan Obaidat, Mohammad F. Tamimi, Ahmad Mumani, et al.
Rapid Prototyping Journal (2024)
Closed Access | Times Cited: 1


Ingenius (2024), Iss. 31
Open Access
Surrogate constitutive model using artificial neural networks for the elastoplastic behavior of materials from fused filament fabrication
Estêvão Santos Laureano da Cunha, David Lucas Pereira, Gustavo Roberto Ramos, et al.
Progress in Additive Manufacturing (2024)
Closed Access
Study on material behaviours of additively manufactured high-impact polystyrene using artificial neural networks
Phan Quoc Khang Nguyen, Nima Zohdi, Y. X. Zhang, et al.
Progress in Additive Manufacturing (2024)
Open Access
Prediction of abrasive wear and surface hardness of printed parts by SLA technology
Pablo Muñoz, O. Villena-López, Leticia Mayorga-Ases, et al.
Ingenius (2024), Iss. 31, pp. 19-31
Open Access
Ensuring Part Quality for Material Extrusion by Developing a Methodology for Use-Case-Specific Parameter Set Determination Using Machine Learning Models
Carsten Schmidt, Rainer Griesbaum, Jan T. Sehrt, et al.
Journal of Manufacturing and Materials Processing (2024) Vol. 8, Iss. 2, pp. 51-51
Open Access
A Quality Prediction Method for Dual-Nozzle FDM Molded Parts Based on CIWOA–BP
Binghui Ji, Mengyang Cui, Jian Mao, et al.
Fibers and Polymers (2024) Vol. 25, Iss. 5, pp. 1913-1923
Closed Access
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