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A Directional Graph Framework to Integrate Engineering Data with Application to Chemical Process

https://doi.org/10.2139/ssrn.4605353
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inferredcites →https://doi.org/10.1016/0031-3203(91)90073-eopenalex-extracted
A probabilistic Hough transform
inferredcites →https://doi.org/10.1016/0031-3203(94)90116-3openalex-extracted
Isolating symbols from connection lines in a class of engineering drawings
inferredcites →https://doi.org/10.1016/0098-1354(79)80079-4openalex-extracted
An algorithm for diagnosis of system failures in the chemical process
inferredcites →https://doi.org/10.1016/0951-8320(95)00052-4openalex-extracted
Digraph-based models for automated HAZOP analysis
inferredcites →https://doi.org/10.1016/j.compchemeng.2008.10.006openalex-extracted
Learning HAZOP expert system by case-based reasoning and ontology
inferredcites →https://doi.org/10.1016/j.compind.2020.103198openalex-extracted
Reducing human effort in engineering drawing validation
inferredcites →https://doi.org/10.1016/j.compind.2021.103442openalex-extracted
Extraction of dimension requirements from engineering drawings for supporting quality control in production processes
inferredcites →https://doi.org/10.1016/j.compind.2022.103656openalex-extracted
Engineering Change Risk Assessment: Quantitative and qualitative change characterization
inferredcites →https://doi.org/10.1016/j.compind.2022.103697openalex-extracted
Graph neural network-enabled manufacturing method classification from engineering drawings
inferredcites →https://doi.org/10.1016/j.compind.2022.103849openalex-extracted
Industrial safety management in the digital era: Constructing a knowledge graph from near misses
inferredcites →https://doi.org/10.1016/j.compind.2023.103856openalex-extracted
Context-aware representation of digital twins’ data: The ontology network role
inferredcites →https://doi.org/10.1016/j.engappai.2004.03.007openalex-extracted
Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets
inferredcites →https://doi.org/10.1016/j.engappai.2006.06.010openalex-extracted
OntoCAPE—A large-scale ontology for chemical process engineering
inferredcites →https://doi.org/10.1016/j.engappai.2022.105697openalex-extracted
Review of artificial intelligence applications in engineering design perspective
inferredcites →https://doi.org/10.1016/j.eswa.2009.06.018openalex-extracted
A fuzzy inference system for pump failure diagnosis to improve maintenance process: The case of a petrochemical industry
inferredcites →https://doi.org/10.1016/j.eswa.2021.115337openalex-extracted
Deep-learning-based recognition of symbols and texts at an industrially applicable level from images of high-density piping and instrumentation diagrams
inferredcites →https://doi.org/10.1016/j.eswa.2023.120509openalex-extracted
Automated method for selecting optimal digital pump operating strategy
inferredcites →https://doi.org/10.1016/j.jlp.2019.103952openalex-extracted
State of research on the automation of HAZOP studies
inferredcites →https://doi.org/10.1016/j.neunet.2020.05.025openalex-extracted
Deep learning for symbols detection and classification in engineering drawings
inferredcites →https://doi.org/10.1016/j.pnucene.2020.103491openalex-extracted
Component detection in piping and instrumentation diagrams of nuclear power plants based on neural networks
inferredcites →https://doi.org/10.1016/j.psep.2021.09.001openalex-extracted
Application of natural language processing in HAZOP reports
inferredcites →https://doi.org/10.1016/s0952-1976(99)00035-4openalex-extracted
Pattern-based fuzzy predictive control for a chemical process with dead time
inferredcites →https://doi.org/10.1016/s0957-4174(97)00092-4openalex-extracted
Knowledge sharing and reuse for engineering design integration
inferredcites →https://doi.org/10.1016/s0957-4174(98)00070-0openalex-extracted
AHA: a knowledge based system for automatic hazard identification in chemical plant by multimodel approach
inferredcites →https://doi.org/10.1093/jcde/qwac056openalex-extracted
End-to-end digitization of image format piping and instrumentation diagrams at an industrially applicable level
inferredcites →https://doi.org/10.1109/34.677283openalex-extracted
Detection of text regions from digital engineering drawings
inferredcites →https://doi.org/10.1109/cvpr.2019.00959openalex-extracted
Character Region Awareness for Text Detection
inferredcites →https://doi.org/10.1109/cvprw50498.2020.00096openalex-extracted
Automatic Digitization of Engineering Diagrams using Deep Learning and Graph Search
inferredcites →https://doi.org/10.1109/icdar.2007.4376991openalex-extracted
An Overview of the Tesseract OCR Engine
inferredcites →https://doi.org/10.1201/9780203752227openalex-extracted
Hazop and Hazan
inferredcites →https://doi.org/10.1205/psep.04055openalex-extracted
PHASuite: An Automated HAZOP Analysis Tool for Chemical Processes
inferredcites →https://doi.org/10.48550/arxiv.2108.13912openalex-extracted
Automatic digital twin data model generation of building energy systems from piping and instrumentation diagrams
inferredcites →https://doi.org/10.5220/0007376401630172openalex-extracted
Automatic Information Extraction from Piping and Instrumentation Diagrams
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-snapshot
You Only Look Once: Unified, Real-Time Object Detection
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