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Engineering Drawing Extraction

Business Need​

Extract structured data from engineering drawings and technical schematics at scale, including part numbers, dimensions, materials, tolerances, and revision information, while automatically mapping dependencies between related components and assemblies.

Solution Overview​

This solution leverages AI Workflows to deliver automated technical documentation processing:

Step 1: Drawing Ingestion

  • Data Source: PDF files containing engineering drawings stored in S3 buckets
  • Scheduling: Automated pipeline runs weekly to process new or updated drawings

Step 2: Data Extraction

Advanced large language models extract structured information:

  • Part Identifiers: Part numbers, assembly codes, drawing numbers
  • Specifications: Dimensions, tolerances, materials, finishes
  • Metadata: Revision numbers, dates, approval signatures, change notices

The AI Workflow uses specialized technical document understanding to maintain precision even with handwritten annotations or legacy drawings.

💡Pro Tip

Create validation rules for critical fields (e.g., part numbers must match company format regex). The AI Workflow can flag drawings where extracted data doesn't match expected patterns, reducing downstream errors in bill-of-materials systems.

Step 3: Dependency Analysis

The workflow builds a comprehensive dependency graph:

  • Identifies assembly relationships (parent-child component hierarchies)
  • Maps referenced parts and sub-assemblies
  • Detects cross-references between drawings

Step 4: Structured Output Generation

Results are delivered in below formats:

  • JSON: Structured data for each drawing with all extracted attributes
  • CSV: Tabular format for import into PLM/ERP systems

How It's Used in Practice​

This solution operates as a scheduled batch process with API-triggered on-demand processing:

Weekly Batch Processing:

  • Engineering team uploads new/revised drawings to designated S3 bucket
  • AI Workflow runs automatically on a weekly basis
  • Outputs are written back to S3 and metadata loaded into Snowflake data warehouse

On-Demand Processing (via API):

  • Urgent drawing updates can be processed immediately
  • API endpoint accepts single drawing or small batch

The system has processed over 50,000 engineering drawings with 90%+ straight-through processing rate (no human intervention required).

✨Key Outcomes

Key achievements:

🚀 Reduction in manual data entry​

Eliminated hours per week of manual drawing data transcription

🔍 Automated dependency mapping​

Created comprehensive part relationship graphs across 45,000+ drawings

✅ 90%+ straight-through processing rate​

Most drawings require no human review or correction

⚡ 2-4 hour batch processing​

Weekly processing of 500-2,000 drawings completed overnight

Additional Information​