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Top four Obstacles to Overcome when Implementing Predictive Maintenance

When it comes to an effective building management system, successful predictive maintenance is something of a holy grail. By being able to use information obtained from the machinery or systems which require maintenance in order to predict when maintenance is needed to prevent failure or a diminution in performance, it’s possible to significantly reduce downtime as well as prevent the costs associated with a breakdown. Unfortunately, when it comes to facilities management, there are a number of obstacles which can prevent predictive maintenance being as effective as it should be. Here we consider four of the main barriers to predictive maintenance, as well as provide options to overcome them, using a suitable residential management system or building management software.

Insufficient data

The idea behind predictive maintenance is that data will be obtained from the systems in use (normally through the use of sensors). Sophisticated facility management software algorithms then use this data to predict when maintenance is needed. Particularly when the system is new, there may not be enough data to form a sensible view. Luckily, a good facility management system can be programmed to collect data more frequently, ensuring this problem is rapidly overcome.

Insufficient failure data

In order for predictive maintenance to work as part of building management, the caretaker, STRATA manager or another responsible member of staff needs to know what the data which shows imminent failure looks like. If the systems are well-maintained, this may not exist! Luckily, failure can be simulated, allowing appropriate data to be obtained for future reference without the need for a failure to actually occur.

Knowing what a failure looks like, but not being able to predict one

Developer management system algorithms are only as good as the programming they’ve received. In many cases, redefining the parameters for information on the developer management software can result in it becoming clearer what data patterns are associated with imminent failure. It’s also helpful to classify what failure actually means to your organisation – a clear definition makes it easier to see when one is more likely.

Not understanding how to perform predictive maintenance

If you are more used to maintaining a residential website or specialise in residential communication, working out how best to use your defect management software/system can be a challenge. If using predictive maintenance is critical to your facility, it’s possible to obtain suitable training in order to be clear about how best to use the software you have in order to achieve your aims.

As specialists in the software needed for successful building maintenance, our MYBOS property management software offers all the facilities needed to perform effective, on-going predictive maintenance in a wide range of different environments. Get in touch to find out more.

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