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Advanced Monitoring of Manufacturing Process through Video Analytics.

Nisar Hakam^1,2, Khaled Benfriha¹, Vincent Meyrueis¹

¹Arts et Métiers, Institute of Technology (AMIT), 75013 Paris, France.

Sensors (Basel, Switzerland)

|July 13, 2024

Summary

This study introduces an edge-based vision system for real-time monitoring of CNC lathe manufacturing. The system uses image processing to detect parts, measure parameters, and assess tool health, enhancing industrial process control.

Keywords:

data deviation detection digitization industry 4.0 machine video analytics visual

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Area of Science:

Industrial Engineering
Computer Vision
Manufacturing Technology

Background:

Digitization is transforming industrial monitoring.
Real-time data analysis is crucial for dynamic process oversight.
Vision systems offer rich data for manufacturing insights.

Purpose of the Study:

To propose an edge-based vision system for real-time monitoring of CNC lathe manufacturing.
To leverage image processing for in-line quality assessment.
To evaluate the system's deployment efficiency, accuracy, and responsiveness.

Main Methods:

Designing and integrating video modules at the production line edge.
Utilizing image processing techniques for real-time analysis.
Detecting raw parts, measuring process parameters, assessing tool status, and checking roughness.

Main Results:

The proposed method enables real-time detection of raw parts.
Process parameters, tool status, and surface roughness are accurately assessed.
The system's efficiency in deployment, accuracy, and responsiveness is evaluated.

Conclusions:

Edge-based vision systems can effectively monitor CNC manufacturing processes in real time.
Image processing techniques are suitable for in-line quality control.
Future work can integrate edge metadata with AI for predictive maintenance.