ArticleMaterials (Basel, Switzerland)2023
Investigation and Optimization of Effects of 3D Printer Process Parameters on Performance Parameters.
Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Synergistic Optimisation of Surface Properties and Surface Quality of FDM ABS Specimens Based on RSM and CWOA.Polymers · 2026Article
- Research progress of 3D-printed PLGA scaffolds for the treatment of bone defects.Biomedical engineering online · 2025Review
- Three-Dimensional-Printed Isoniazid Chewable Gels for On-Demand Latent Tuberculosis Treatment in Children.Pharmaceutics · 2025Article
- Advanced Machining Technology for Modern Engineering Materials.Materials (Basel, Switzerland) · 2024Article
- Synergistic Effect of Carbon Micro/Nano-Fillers and Surface Patterning on the Superlubric Performance of 3D-Printed Structures.Materials (Basel, Switzerland) · 2024Article
- Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance.Polymers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Professionals in industries are making progress in creating predictive techniques for evaluating critical characteristics and reactions of engineered materials. The objective of this investigation is to determine the optimal settings for a 3D printer made of acrylonitrile butadiene styrene (ABS) in terms of its conflicting responses (flexural strength (FS), tensile strength (TS), average surface roughness (Ra), print time (T), and energy consumption (E)). Layer thickness (LT), printing speed (PS), and infill density (ID) are all quantifiable characteristics that were chosen. For the experimental methods of the prediction models, twenty samples were created using a full central composite design (CCD). The models were verified by proving that the experimental results were consistent with the predictions using validation trial tests, and the significance of the performance parameters was confirmed using analysis of variance (ANOVA). The most crucial element in obtaining the desired Ra and T was LT, whereas ID was the most crucial in attaining the desired mechanical characteristics. Numerical multi-objective optimization was used to achieve the following parameters: LT = 0.27 mm, ID = 84 percent, and PS = 51.1 mm/s; FS = 58.01 MPa; TS = 35.8 MPa; lowest Ra = 8.01 m; lowest T = 58 min; and E = 0.21 kwh. Manufacturers and practitioners may profit from using the produced numerically optimized model to forecast the necessary surface quality for different aspects before undertaking trials.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.