When it comes to equipment failure, there are a few interesting trends that we see. In particular, we can see some of the challenges of effective reliability planning.
Asset failures may result from various causes. The reality of what causes your equipment to fail may be surprising:
If a machine fails, it may be tempting to think it’s just wearing out. However, that’s often not the case. More often than not, you can’t predict equipment failures based purely on the age of an asset.
Again, you can’t reliably chart equipment failures on a calendar. When you think how most preventive maintenance programs are strictly time-based, that gets to be problematic.
With the apparently random nature of equipment failure, proper data management is vital. However:
While facilities are trying to deal with equipment failure, they are often forced to do so on a reactive basis—i.e. once the equipment fails. Lack of knowledge of what tends to fail makes truly effective preventive maintenance nearly impossible.
In other words, they don’t know how well their machines and other assets should be performing. On top of that, many of them don’t understand why they need to understand those performance targets. Without that target value in mind, it’s hard to make meaningful reliability plans.
Given the lack of data and target values, the following facts aren’t surprising:
When measuring success, most maintenance teams regard rapid response, not effective prevention, as the objective. However, there are efforts being made to change that.
Most companies do try, but very few are actually as successful as they’d like to be. It may be related to lack of data, or it might simply be challenging to shift the team’s paradigm.
Do you find this interesting? So do we. Read more maintenance stats here.
From the data, we can see that improving equipment reliability ultimately comes down to shifting your maintenance team’s outlook on their purpose while collecting adequate data to inform maintenance planning.
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