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20242026
most citedLeveraging Vision-Language Models for Manufacturing Feature Recognition in CAD Designs

2 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CE2026

Context-Aware Mapping of 2D Drawing Annotations to 3D CAD Features Using LLM-Assisted Reasoning for Manufacturing Automation

Muhammad Tayyab Khan, Lequn Chen, Wenhe Feng +1

Manufacturing automation in process planning, inspection planning, and digital-thread integration depends on a unified specification that binds the geometric features of a 3D CAD m…

cs.IR2025

Large Language Model Powered Decision Support for a Metal Additive Manufacturing Knowledge Graph

Muhammad Tayyab Khan, Lequn Chen, Wenhe Feng +1

Metal additive manufacturing (AM) involves complex interdependencies among processes, materials, feedstock, and post-processing steps. However, the underlying relationships and dom…

cs.CV2025

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…

cs.CE20242 cited

Leveraging Vision-Language Models for Manufacturing Feature Recognition in CAD Designs

Muhammad Tayyab Khan, Lequn Chen, Ye Han Ng +3

Automatic feature recognition (AFR) is essential for transforming design knowledge into actionable manufacturing information. Traditional AFR methods, which rely on predefined geom…

cs.AI20241 cited

Automatic Feature Recognition and Dimensional Attributes Extraction From CAD Models for Hybrid Additive-Subtractive Manufacturing

Muhammad Tayyab Khan, Wenhe Feng, Lequn Chen +3

The integration of Computer-Aided Design (CAD), Computer-Aided Process Planning (CAPP), and Computer-Aided Manufacturing (CAM) plays a crucial role in modern manufacturing, facilit…