Preventative vs Predictive Maintenance and why you need to get on board

[Anonymous user]

Originally published on the Senseye blog 

When talking to people we’ve found that the terms Preventative and Predictive can often mentally overlap; yet there’s such a marked difference in implementation techniques and real-world effects that it’s important to clearly define both before we get into their pros, cons and why Predictive Maintenance is the only future for manufacturers. 

Preventative maintenance relies heavily on a manufacturer-specified Mean Time Between Failure (MTBF) that dictates on average the length of time between failures of a machine and its components. Maintenance activities are performed before the MTBF number (typically in hours of operations) is exceeded.

Predictive maintenance relies on real-world diagnostic (what the condition currently is) and prognostic (what the condition in the future will be) information from the machine and its components (this could be vibration monitoring for bearings / gearboxes, current monitoring for electric motors, temperature monitoring for fluids, etc.). Maintenance is performed based upon actual condition of the components and their expected Remaining Useful Life (RUL), allowing you to forecast machine failure accurately and avoid it.

The real world isn’t ideal

Unfortunately for these schemes and our neat diagrams, the real-world never conforms to ‘the ideal’ and some compromise is necessary. 

Preventative maintenance doesn’t take into account the actual usage of the machine and cannot in any way indicate potential failure points. Often the things that fail are not what the manufacturer found in their original testing regimes and as machines age their behavior changes considerably. Manufacturer supplied MTBF numbers are usually very conservative as the tendency to over-maintain is generally less expensive than failure and the downtime that it brings.

Not only is the planned maintenance interrupting operations (downtime) but the unplanned breakdowns will cause extra downtime – sometimes even just before a planned maintenance event. In the real world, this scheme becomes increasingly expensive and inefficient as the machine ages. 

Predictive maintenance in the real world will more than likely have an element of planned maintenance for increased assurance but these will tend to be fewer and less disruptive. Regular condition based maintenance based upon prognostics information enables avoidance of unplanned downtime. In some cases, condition indicators may appear before a planned maintenance event, opportunistic maintenance could then be merged into the already planned maintenance event to give an extra efficiency boost.

Weigh-in

Predictive Maintenance driven by reliable diagnostics and prognostics is the clear winner in terms of optimizing productivity and minimizing downtime. The single caveat for adopters is that it is entirely real-world driven, requiring extensive data to be collected and the upfront investment for this can look daunting, although that’s changing as Industry 4.0 and the IIoT gain pace and the cost of sensors comes down. Newer machinery even comes with sensors and data collection built-in to assist with predictive maintenance. 

The greatest improvement over preventative maintenance is that it allows you to maintain for appropriate usage and condition, not purely on MTBF. You save money by not only having fewer deep maintenance events but fewer unplanned downtime events – you’ll have been warned about the condition of the component ahead of time and will have the opportunity to perform corrective maintenance before it becomes a downtime and productivity issue. 

Why Predictive Maintenance is the future

Do you like wasting time and money? Didn’t think so. Neither do your competitors. The giant leap that Industry 4.0 brings isn’t in new materials, machines or production techniques. It’s about improving and optimizing what you already have, squeezing every last drop of productivity from your investments. 

Preventative Maintenance is a great way to spend money. Predictive Maintenance is an essential component of staying competitive and being in a position to lead your market. 

Predictive Maintenance is enabled by products like Senseye, helping you to avoid downtime and ensure productivity whilst spending less money. That’s pretty exciting! 

Want to find out more about how Sensey PdM can help optimize maintenance spending and boost productivity? Check out our white paper ‘Harness the Power of Prediction’ or book a demo of Senseye PdM today.