MSTW EndMill: Multi-Sensor Tool Wear Data from End Milling

A multi-sensor dataset for monitoring tool wear in end milling operations. The dataset is 12.2 GB in size and was authored by Sameer Sayyad, last updated on May 20, 2026. It is available under a CC-BY-4.0 license on the figshare platform.

Use Cases

• Predict remaining useful life of milling tools based on multi-sensor signals.
• Train anomaly detection models for tool failure based on sensor data patterns.
• Benchmark signal processing and feature extraction methods for manufacturing sensor data.

Strengths

• Dataset size is 12.2 GB, indicating a substantial volume of sensor data.
• Data is licensed under CC-BY-4.0, allowing for broad reuse and sharing.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.

Provenance

Source

Sameer Sayyad via figshare

Freshness

Last updated 2026-05-20 11:52:10; freshness should be verified.