Reduce Disruption from Fatigue Cameras in Haul Trucks and Avoid Lost Mine Productivity

Mines are known for their stringent operating environments, with safety and productivity being two essential pillars that govern their day-to-day operations. In the past decade, many mining companies worldwide have leveraged reactive driver-facing cameras to mitigate the risks associated with fatigue, such as those from Hexagon OAS or Caterpillar DSS. 

These reactive systems play a valuable role in identifying fatigue in real-time. However, the triggered alarms, though vital for safety, can introduce unexpected disruptions. 

As Fatigue Science, a global leader in predictive fatigue management technology, we appreciate the role these technologies play in enhancing mine safety, and we believe that predictive technology offers a complementary approach to reactive fatigue cameras. Together, we have seen repeated real-world results from the two technologies applied together – minimizing disruptions to operations while preserving the important safety functions of each system.

To understand this, consider a haul truck, a crucial cog in mining operations, working on a tightly controlled schedule to transport material. A fatigue camera detects a potential fatigue event, triggering an alarm that doesn’t immediately halt the truck’s operation, but demands the attention of decision-makers in the control center. Even if the truck isn’t stopped every time, this evaluation process can pull focus from other critical duties, and the result is often minor or major delays. Furthermore, false alarms can add to this challenge, causing unnecessary halts in operations due to fatigue events that sometimes aren’t truly present. 

All of this can potentially lead to missed targets, affecting key productivity metrics like “tons moved per hour” or “cycle times.”

Reducing Alarm Disruptions with Predictive Fatigue Management

An ideal approach to address these challenges is to implement a proactive fatigue management strategy that complements these reactive systems, reducing the likelihood of true alarms and minimizing false ones. Our platform, Readi, offers such a solution. 

The Readi system’s validated predictive technology forecasts individual operators’ fatigue risk levels before the shift starts, enabling shift supervisors to take appropriate measures to manage fatigue proactively. Such measures often include the assignment of additional, well-timed breaks to operators where the need is most warranted, and occasionally include task rotation in more extreme instance. 

Simple proactive measures like these have been shown to reduce the number of camera-based fatigue alarms substantially, minimizing disruption to operations. The resulting effect is improved operational efficiency and enhanced safety without compromising productivity.

This approach was successfully demonstrated in a recent case study at a large Central American copper mine. Upon integrating Readi with their existing Caterpillar DSS system, the mine achieved a 50% reduction in fatigue camera alarms. 

This showcases the seamless integration and synergistic benefits of predictive and reactive fatigue management technologies.

Enhancing Camera Alarm Accuracy with a Second Source of Fatigue Data

Another crucial benefit of incorporating predictive technology like Readi is the provision of a second source of data. Besides reducing false alarms, this additional data layer offers an extra layer of validation for the reactive systems, ensuring more accurate fatigue detection. 

Readi’s integration with Hexagon OAS, for instance, provides the ability to see each operator’s predicted fatigue level (“ReadiScore”) side-by-side with the video feed when the camera has registered an alarm. When alarms do trigger, supervisors can use the predictive data from Readi to make more informed decisions about whether to pull a worker off a task or allow them to continue, minimizing productivity disruptions without compromising safety.

Marcobre’s Mina Justa Mine, a leading Peruvian mining firm, effectively illustrates this concept. 

The mine uses both Readi and the Caterpillar DSS camera system to manage fatigue. 

According to Caterpillar, an acceptable index of fatigue events is 0.05 events per hour worked, or one event per every 20 hours. By the end of 2022, Marcobre recorded a mere 0.002 fatigue events per hour worked, indicating a fatigue event every 500 hours – 95% lower than the benchmark figure. This outcome emphasizes the significant improvements possible with a proactive approach towards fatigue management.

Ensuring a Safer, More Productive Future

At Fatigue Science, we believe in the power of data-driven decisions and proactive strategies in managing fatigue. We respect the decision of customers who choose to deploy camera technologies like Hexagon OAS and Caterpillar DSS, and believe that for such mines, a complementary approach that leverages predictive technology such as ours is the best way to ensure not only safety, but efficient operations that deliver the most from their technology investments.

As we continue to partner with mining sites worldwide, we are committed to delivering solutions that help our clients improve operational efficiency, reduce fatigue events, and create safer work environments. 

To learn more about how Fatigue Science’s Readi can enhance the safety and productivity of your mining operations while complementing existing reactive systems, please reach out to us. We are excited to collaborate and pave the way for a safer, more productive future in mining.

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