新一代全生命周期质量管理 X AI 解决方案领跑者

Drawing Analysis - CDI

Zero waiting and manual conversion for data transmission from design to manufacturing drawings

An AI+drawing process planning industrial software that utilizes deep learning and large models for intelligent process analysis of engineering drawings. It can automatically identify key process requirements, technical requirements, and quality control requirements in the drawings and generate structured cards for process planning. Compared with traditional computer-aided process planning (CAPP) software, process planning software based on AI large models can make intelligent decisions, adaptive learning, integrate CAD data better and faster, handle complex process requirements simultaneously, and better support personalized, non-standard production. After use, it can greatly improve the efficiency of process engineers in completing process planning.

Core Functions

Resolving Hallucinations

Universal Applicability

After Fine-Tuning, The Accuracy Rate Can Reach Up To 95%.

Continuous Improvement

On the basis of identifying the basic elements of drawings such as diameter or length, contextual understanding is carried out, and in tasks that require accuracy, these measurement data are interconnected to derive meaningful insights, enabling the multimodal recognition capability of large models to meet industrial requirements.

Resolving Hallucinations

Suitable for various types of drawings, including: drawings in different language formats, drawings with geometric dimension tolerances, various irregularly shaped drawings, non-standard drawings, JPG image drawings, PDF format drawings, etc.

Universal Applicability

The innovative method of fine-tuning the large model ensures accuracy and contextual awareness, allowing for a deeper understanding of each drawing change. Scene model fine-tuning can achieve up to 95% accuracy.

After Fine-Tuning, The Accuracy Rate Can Reach Up To 95%.

The platform undergoes rigorous testing on large technical drawing datasets to ensure accuracy and reliability of results. Each update enhances its ability to solve complex challenges.

Continuous Improvement

Resolving Hallucinations

On the basis of identifying the basic elements of drawings such as diameter or length, contextual understanding is carried out, and in tasks that require accuracy, these measurement data are interconnected to derive meaningful insights, enabling the multimodal recognition capability of large models to meet industrial requirements.

Universal Applicability

Suitable for various types of drawings, including: drawings in different language formats, drawings with geometric dimension tolerances, various irregularly shaped drawings, non-standard drawings, JPG image drawings, PDF format drawings, etc.

After Fine-Tuning, The Accuracy Rate Can Reach Up To 95%.

The innovative method of fine-tuning the large model ensures accuracy and contextual awareness, allowing for a deeper understanding of each drawing change. Scene model fine-tuning can achieve up to 95% accuracy.

Continuous Improvement

The platform undergoes rigorous testing on large technical drawing datasets to ensure accuracy and reliability of results. Each update enhances its ability to solve complex challenges.

Product Value

Ultra-High Efficiency

It can quickly process and analyze large amounts of drawing data and automatically complete process card production, which can improve efficiency by at least three times compared to traditional manual review.
Accurate And Consistent

Intelligent recognition and classification of drawings through deep learning algorithms effectively reduce errors caused by human factors. And it can conduct consistency reviews based on preset standards and specifications to ensure that each review result is accurate and reliable.
Traceability

Record all data and information during the review process, including every step of the review and any issues identified. The review results are transparent and facilitate subsequent review and verification work.

Ultra-High Efficiency

It can quickly process and analyze large amounts of drawing data and automatically complete process card production, which can improve efficiency by at least three times compared to traditional manual review.

Accurate And Consistent

Intelligent recognition and classification of drawings through deep learning algorithms effectively reduce errors caused by human factors. And it can conduct consistency reviews based on preset standards and specifications to ensure that each review result is accurate and reliable.

Traceability

Record all data and information during the review process, including every step of the review and any issues identified. The review results are transparent and facilitate subsequent review and verification work.

Get More

Consulting Prices

Recommend the best solution for you
Reservation

One click appointment, expert demonstration
Contact Number

400-105-9339