Overall, the main mistakes I’ve seen with lubricating bearings have to do with either too much lubrication or too little. Too little, and you end up with harmful levels of friction and excess wear. Too much, and you can actually keep rolling parts from working the way they’re supposed to.
Unfortunately, knowing how much lubrication your bearings need often amounts to guesswork. Many maintenance teams lubrication on a routine basis, but a time-based system isn’t always the best. The usual result is over-lubrication, which tends to be wasteful as well as potentially harmful for the equipment.
If your lubrication schedule is too sparse, you end up with under-lubrication. That means more friction for your bearings, increased wear, and premature failure.
So how do you go about solving that situation? I’d suggest moving from a time-based process to a data-based approach.
Ultrasound equipment can do wonders, especially when used in conjunction with a CMMS. Tracking decibel levels can give you a heads up on when bearings are facing too much friction and therefore need lubrication.
Even then, you want to make sure you’re tracking the dB data and not basing decisions merely on what the equipment sounds like. That’s another common mistake maintenance teams make. They base their decisions on subjective interpretations of the data rather than actual trends.
This type of data tracking is actually the core of predictive maintenance. By setting up ultrasound sensors at each core piece of equipment and tracking the data, you’ll be able to tell when each asset needs lubrication. That way, you’ll only lubricate as often as it’s needed and prolong the life of your bearings.
So, to summarize and answer your question, the main mistakes are:
To resolve these problems:
Doing so should help you optimize your lubricating processes and increase the life of your assets.
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What Is Ultrasound Analysis (UA)?
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