VALIDATION STRATEGY FOR INDUSTRIAL 4.0 AI/ML MODEL FOR VISION-BASED QUALITY CONTROL

7 Pages

The paper presents a validation strategy for AI/ML models deployed in smart manufacturing to enable real-time, vision-based quality control. It discusses a hybrid test approach using both real and simulated environments with NVIDIA Jetson edge AI devices, leveraging Python-based automation frameworks for testing. Key validation factors include data quality, model performance, explainability, generalizability, and integration. The aim is to ensure reliable, efficient, and scalable AI deployment while minimizing CapEx and OpEx risks.

Join for free to read

Ebook Digital Transformation in Life Sciences With Validation 4.0

Vendor Sheet NetSPI AI/ML Penetration Testing

White Paper Choosing the right Validation Approach for Asset Management…

White Paper AFFORDABLE DISAGGREGATED STORAGE FOR KUBERNETES AI/ ML/DL…

More from Happiest Minds

White Paper Choosing the right Validation Approach for Asset Management…

Guide Quality Assurance in the Era of LLM’s

White Paper Microsoft New Model of DaaS

White Paper Industrial UPS Monitoring Solution Using Azure IoT

White Paper

VALIDATION STRATEGY FOR INDUSTRIAL 4.0 AI/ML MODEL FOR VISION-BASED QUALITY CONTROL

VALIDATION STRATEGY FOR INDUSTRIAL 4.0 AI/ML MODEL FOR VISION-BASED QUALITY CONTROL

You Might Also Like

More from Happiest Minds