Machine Vision Label Validation for Motor Manufacturing

Project Overview

Customer Focus

An Automotive manufacturing plant aimed to enhance production reliability, digital visibility, and system responsiveness across its plant operations. With increasing production volumes and performance expectations, the customer required a future ready automation architecture that could improve machine uptime, ensure seamless data exchange, and strengthen operational transparency without replacing their complete existing infrastructure.

Requirement

The ID MCU production line required a robust vision inspection framework to validate homologation labels on motors with complete digital traceability. The objective was to strengthen compliance control, ensure inspection accuracy, and establish structured image documentation while maintaining uninterrupted coordination with the existing PLC driven automation architecture.

Challenges

Absence of structured image storage hierarchy limited traceability efficiency. Hard drive capacity was not actively supervised, creating risk of storage saturation during extended production runs. There was no mechanism to transmit storage threshold alerts to the machine controller. Compliance documentation and data reliability required technical reinforcement.

Key Constraints

Unmonitored IPC storage capacity
Non standardized image archiving structure
No controller linked storage alarm feedback

Our Solution

We integrated a Cognex vision system engineered to perform precise label detection and classification solution on the ID MCU line, combining automated image archival with a structured hierarchical folder architecture. The system was aligned to ensure deterministic OK NG segregation, continuous IPC D drive supervision, interval based storage evaluation, and threshold driven alert generation. Upon reaching predefined capacity limits, the solution transmits an alarm bit directly to the PLC, ensuring controlled runtime performance and proactive infrastructure protection within the manufacturing environment.

Implementation Highlights

Structured OK and NG image categorization
Automated D drive utilization tracking
PLC integrated alarm bit at 75 percent Hard Drive usage

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