5 Condition Monitoring Fails (and How to Avoid Them)
Uptime. It’s always your goal. Yet the cost to proactively maintain 100% uptime can outweigh the benefits. That’s why some businesses operate under a “run to fail” model. But your energy operation can’t afford a break-and-fix approach, either. Too many risks and too many surprises.
Condition monitoring enables you to reduce the cost of performing preventive maintenance yet avoid the sudden expenditures to repair or replace failed assets.
Not all condition monitoring is the same, however. Fact is, there are five critical considerations when implementing an effective monitoring initiative. Each is an opportunity for your condition monitoring effort to fail.
1) Not selecting the right condition indicators.
You run an incredibly complex energy system. The key indicators of equipment health and longevity vary greatly depending on what parameters are being monitored on the Asset. For example, there are more than 50 parameters (with 150+ data pints) that can be monitored on a power transformer and still it becomes difficult to estimate transformer health. In fact, sometimes more data actually hinders accurate assessment. Working with your design engineers, we help you identify all the key indicators, so you get a full view of your system assets, and feel confident you’re minimizing the potential for an unexpected failure.
2) Choosing the wrong measurement tools/technologies.
Even when you’ve identified the right asset characteristics to monitor, it’s important to select the smartest technologies to do the job. Working with an OEM-agnostic partner can help you be sure you have the best tech for every critical data-gathering point. Making the best use of offline test data is also critical in health estimation and monitoring systems. If you have the possibility to use offline test data, it’s always an advantage.
3) Monitoring too little.
The effectiveness of monitoring relies on how much data is gathered. Too little and you still run the risk of a surprise failure. The Qualitrol team can advise you on the frequency and depth of data required to be predictive and cost-effective.
4) Overlooking proper data analysis.
Successful condition monitoring is a multi-layered endeavor. Even if have the right equipment collecting all the right data, taking time and energy to analyze is properly is key. Only then can you be sure when maintenance is required. Some of this can automated. Some requires human analysis. We help you with both.
5) Ignoring maintenance suggested by condition monitoring results.
Amazingly, some energy operations can have all the data and analytics in place, yet still choose not to perform the maintenance that’s indicated. Maybe there’s a degree of human discretion. But in most cases, when maintenance is indicated, it should be performed otherwise there was no point to begin with.
To discuss optimizing your Condition Monitoring system–and how you can avoid the high cost of asset failure–talk to Qualitrol today.