Process Defects Knowledge Modeling in Laser Powder Bed Fusion Additive Manufacturing: An Ontological Framework

No abstract is available for this paper.

• Publication year

  2023

• Venue

  Social Science Research Network

• Publication date

  2023-08-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.2139/ssrn.4382500
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Ontology Network-Based In-Situ Sensor Selection for Quality Management in Metal Additive Manufacturing

  2022cited by this paper
• Ontology-based Process Map for Metal Additive Manufacturing

  2021cited by this paper
• Ontology-Driven Learning of Bayesian Network for Causal Inference and Quality Assurance in Additive Manufacturing

  2021cited by this paper
• Defect inspection technologies for additive manufacturing

  2021cited by this paper
• Defects in Metal Additive Manufacturing Processes

  2020cited by this paper
• Machine learning and knowledge graph based design rule construction for additive manufacturing

  2020cited by this paper
• Ontology-based knowledge representation for additive manufacturing

  2019cited by this paper
• Taxonomy of Gas Turbine Blade Defects

  2019cited by this paper
• Common defects and contributing parameters in powder bed fusion AM process and their classification for online monitoring and control: a review

  2018cited by this paper
• The development of an ontology for describing the capabilities of manufacturing resources

  2018cited by this paper
• Process defects and in situ monitoring methods in metal powder bed fusion: a review

  2017cited by this paper
• Defect Formation Mechanisms in Selective Laser Melting: A Review

  2017cited by this paper
• A Design for Additive Manufacturing Ontology

  2016cited by this paper
• The protégé project: a look back and a look forward

  2015cited by this paper
• Experimental designs for identifying causal mechanisms

  2013cited by this paper
• OntoQuery: easy-to-use web-based OWL querying

  2013cited by this paper
• SQWRL: A Query Language for OWL

  2009cited by this paper
• SWRL : A semantic Web rule language combining OWL and ruleML

  2004cited by this paper
• Knowledge level modelling: concepts and terminology

  1998cited by this paper

• Intelligent cyber-physical production systems driven by knowledge and data: contributions, limitations, and applications in the aerospace industry

  2026cites this paper
• Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

  2026cites this paper
• Process development for green laser LPBF of pure Cu using dimensionless numbers

  2025cites this paper
• A knowledge graph-based standardized modeling and quantitative retrieval method for product defect analysis-related knowledge

  2025cites this paper
• Distortion Minimization in Reverse Engineering for Additive Manufacturing: An Integrated 3D Scanning and Simulation Framework

  2025cites this paper
• RAMPSeg: A robust calibration-free image segmentation method for reliable melt pool analysis in laser powder bed fusion

  2025cites this paper
• Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data

  2024cites this paper
• An ontology of eco-design for additive manufacturing with informative sustainability analysis

  2024cites this paper
• Combined Use of Acoustic Measurement Techniques with X-ray Imaging for Real-Time Observation of Laser-Based Manufacturing

  2024cites this paper