Image Classification for End-of-Line Quality Control in Manufacturing

Ehrenmüller's AI-powered image classification solution enables manufacturers to automate and enhance end-of-line quality control processes. Developed and proven in production environments for agricultural machinery manufacturers, this solution compares real-time camera images of finished products against configuration data from Manufacturing Execution Systems (MES) to detect missing or faulty components.

Key Capabilities:

The AI model performs object detection on images captured at the quality inspection station, identifying components such as work lights, mirrors, and other configurable parts. It then cross-references detected components against the customer-specific and country-specific configuration stored in the MES system. Deviations and errors are visually highlighted for production staff, enabling targeted corrections before delivery.

GDPR-Compliant Operations:

A dedicated AI model runs in parallel to automatically anonymize any workers visible in captured images, ensuring full compliance with data privacy regulations without disrupting the inspection workflow.

Cloud-Based Architecture on AWS:

The solution leverages AWS cloud infrastructure for real-time AI inference. Amazon Rekognition or Amazon SageMaker can be used to host and run custom object detection models, while AWS IoT Greengrass enables edge inference on on-premises industrial PCs connected to networked cameras at the inspection station. Amazon RDS or Amazon DynamoDB stores detection results, enabling analytics on recurring defects and continuous model optimization via Amazon SageMaker pipelines. Amazon S3 provides scalable image storage, and Amazon CloudWatch enables monitoring of inference performance across sites. The architecture supports deployment as an Industrial Cloud Product across multiple manufacturing sites.

Benefits:

• Increased efficiency in quality inspection processes
• Reduced manual workload for repetitive verification tasks
• Employee-friendly integration into existing production workflows
• Data-driven insights for identifying frequent defect patterns
• Scalable deployment across multiple production facilities using AWS infrastructure

The solution is designed for mid-market and enterprise manufacturers seeking to augment their quality control with AI while maintaining seamless integration with existing MES systems and production processes.