Prevent Catastrophic Engine Failure with Predictive Maintenance

Not all failures begin with obvious wear.

In a recent case, one of four engines powering a remote mine site began showing a steady increase in nitration, oxidation, and soot levels, despite no abnormal wear metals being detected.

The lab results were classified as normal. However, the operating context told a different story.

These engines had been closely monitored since commissioning, and the pattern did not align with expected operating conditions. The combination of signals pointed to abnormal combustion and a developing failure mechanism already in motion.

The alert was escalated to critical, and a full air-box inspection was recommended immediately.

The inspection identified a bent valve in one of the cylinders.

The repair itself was relatively straightforward:

- Cylinder head replacement
- Compression checks completed
- Engine returned to service

What was avoided was far more significant: a catastrophic engine failure that would have taken a critical power unit offline and disrupted site operations.

Estimated breakdown avoidance: $196,000.

Most operations already have large volumes of condition monitoring data. The challenge is identifying when a “normal” result does not reflect operational reality, especially when the early indicators are subtle and distributed across multiple data sources.

That’s where operational context, reliability expertise, and the ability to connect signals early become critical.

If improving how your team identifies and acts on emerging failures is a priority, we’d be glad to talk.

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