NCBI PubMed Central
open access
Machine Learning-Driven Prediction of Manufacturing Parameters and Analysis of Mechanical Properties of PC-ABS Specimens Produced by the Fused Deposition Modeling Additive Manufacturing Method.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
Checking your browser before accessing pmc.ncbi.nlm.nih.gov ... Click here if you are not automatically redirected after 5 seconds.
Related documents
- Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review#320276
- Dataset on the reproducibility of UHPC mechanical properties under a fixed recipe with controlled production variability.#375273
- Classification of wear mechanisms in hot forming of aluminium alloy by machine and deep learning approaches#288029
- Uncertainty Quantification and a Model Reduction Procedure of a Laser Fusion Additive Manufacturing Simulation#1106975
- Trustworthy Artificial Intelligence for Real-Time Quality Assurance in Additive Manufacturing#823327
Record · ID 12763 · SHA-256 b87e9d5184d5cb3e
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive