ShovelMetrics™ Articles

Artificial Intelligence-Based Monitoring of Mining Shovel Tooth Wear


Tooth Wear Monitoring


Mining shovel teeth are consumable parts that wear unevenly. To schedule change-outs, mine personnel typically measure each shovel tooth manually; this paper presents a novel AI-based alternative – ShovelMetrics™ Tooth Wear Monitoring.

In this article you will understand:

  • How ShovelMetrics™ uses deep neural networks to monitor the wear rate of each tooth.

  • How our AI-based approach performs significantly better than a human labelling images and provides tooth measurements with an average accuracy of ~92%.

  • How an average oil sand mine can save USD $50K per shovel per year by monitoring tooth wear with ShovelMetrics™ instead of using traditional manual methods.

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