SmartManuAD/Smart-Manufacturing-AD

Repository linked to "Anomaly detection in Smart-manufacturing era: A review"

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This project helps manufacturing engineers and data analysts detect anomalies in smart manufacturing processes. It takes real-time operational data from factory sensors and identifies unusual patterns that indicate potential machine faults or upcoming breakdowns. The outcome is a better understanding of system health and insights into the most suitable anomaly detection methods for various industrial environments, helping to prevent costly unscheduled stops.

No commits in the last 6 months.

Use this if you need to analyze large volumes of sensor data from smart factories to proactively identify equipment malfunctions or process irregularities.

Not ideal if your manufacturing environment does not generate real-time operational data from embedded sensors or if you are not focused on fault detection.

Smart-Manufacturing Predictive-Maintenance Quality-Control Industrial-Automation Operational-Efficiency
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 16 / 25

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Stars

20

Forks

6

Language

Python

License

GPL-3.0

Last pushed

Aug 20, 2023

Commits (30d)

0

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