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A Multi-Stage Hybrid Framework for Automated Interpretation of Multi-View Engineering Drawings Using Vision Language Model
Muhammad Tayyab Khan, Zane Yong, Lequn Chen +3
Engineering drawings are fundamental to manufacturing communication, serving as the primary medium for conveying design intent, tolerances, and production details. However, interpr…
From Drawings to Decisions: A Hybrid Vision-Language Framework for Parsing 2D Engineering Drawings into Structured Manufacturing Knowledge
Muhammad Tayyab Khan, Lequn Chen, Zane Yong +3
Efficient and accurate extraction of key information from 2D engineering drawings is essential for advancing digital manufacturing workflows. Such information includes geometric di…
Automated Parsing of Engineering Drawings for Structured Information Extraction Using a Fine-tuned Document Understanding Transformer
Muhammad Tayyab Khan, Zane Yong, Lequn Chen +3
Accurate extraction of key information from 2D engineering drawings is crucial for high-precision manufacturing. Manual extraction is slow and labor-intensive, while traditional Op…
Fine-Tuning Vision-Language Model for Automated Engineering Drawing Information Extraction
Muhammad Tayyab Khan, Lequn Chen, Ye Han Ng +3
Geometric Dimensioning and Tolerancing (GD&T) plays a critical role in manufacturing by defining acceptable variations in part features to ensure component quality and functionalit…