Control of material quality with computer vision
BUSINESS CHALLENGE
Manual quality inspections in the manufacturing process were slow and error-prone, leading to defects and inefficiencies. Is needed an automated system to accurately detect product defects in real-time and integrate seamlessly into their production line.
SOLUTION IMPLEMENTED
Implemented an AI-powered quality control system that integrates computer vision to detect defects in real time. IoT Hub collects data from sensors and cameras on the production line, while Event Hub streams this data to Databricks, where machine learning models analyze it for potential defects. This data is then stored in a Cosmos DB
RESULTS & ROI
SATISFACTION
Improved manufacturing process times, leading to higher customer satisfaction and loyalty.
QUALITY
Errors are identified in the manufacturing process, leading to less errors in the final product.
SAVINGS
Detecting errors in this early phase, leads to savings in manufacturing costs and other processes.
TECHNOLOGY
DATA PLATFORM
An Iot Hub controls the extraction of data, which is passed to a Databricks through an Event Hub, storing the result in a Cosmos.
SERVING
Real-time insights integrated into interactive dashboards to visualize production metrics and possible pieces errors.
AI
Purview to ensure data quality, compliance, and secure governance across all data.