IoT For Predictive Maintenance

Or rather how the Industrial Internet of Things helps Predictive Maintenance (maintaining a machine before it breaks down and causes downtime). 

It’s no secret that predictive maintenance is a tricky subject. The idea of being able to maintain your machines, just before they are about to fail represents an ideal case for a number of reasons: 

  • No need to keep inventory of spares
  • You avoid over-maintaining your equipment (expensive)
  • You avoid failure and have a good idea of exactly what condition the machine is in 

Usually a manufacturer will specify a Mean Time Between Failures (MTBF) or Mean Time To Failure (MTTF). Whilst they sound similar, there is a distinction in that MTTF is generally used to measure non-reparable systems. Maintenance will be done periodically at times that are less than the Mean Time Between Failures. Statistically this should ensure that a failure ‘never’ occurs as you are always maintaining and ‘resetting’ the MTBF period, unfortunately it doesn’t really work like that in the real world. 

Predictive maintenance can be as simple as a skilled operator hearing something different about the machine that he uses day-to-day but when we talk about it in the context of the Industrial IoT. We’re talking about using constant, in-situ monitoring of many variables like vibration, temperature, pressure, current, etc. depending on the situation – these are called condition indicators. The in-situ monitoring is typically small low-cost sensing and processing devices with connections to the internet – streaming data to the cloud. 

The beauty of the IIoT is that we can monitor these complex parameters cheaply and easily – without requiring manual inspection. 

So we can monitor things easily but what does that really mean? With advanced prognostics (figuring out when machines will fail before they do, based upon their usage and condition indicators) we can move away from simple MTBF / MTTF based maintenance. That means potentially saving money (the manufacturer will be conservative and lean towards over-maintenance) but crucially having better quality information about what needs maintaining and why. 

The IIoT helps predictive maintenance by giving a reliable, inexpensive source of information for products like Senseye to help you to avoid downtime whilst spending less money. That’s pretty exciting! 

Want to learn more about our new, easy-to-use diagnostics, prognostics and condition monitoring product to help you to avoid downtime? Download our free flyer here:

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