What’s the Difference Between Preventive, Proactive, and Predictive Maintenance?
Downtime in a plant or facility leads to lost productivity. It disrupts operations, causes maintenance staff to divert time from scheduled projects, and can have significant negative business implications, including lost revenue, significant unplanned expenses, missed deadlines and damage to a company’s reputation.
To avoid these problems, manufacturers and facility and plant managers are moving away from traditional maintenance methods where you wait for something to break, and then you fix it. Reactive approaches like this result in disruptions and unplanned downtime.
A better approach is preventive maintenance, which is a routine for periodically inspecting equipment with the goal of noticing small problems and fixing them before major ones develop The main goal behind preventive maintenance is for the equipment to make it from one planned service to the next without any failures.
Companies that employ a preventive maintenance strategy often make use of manufacturer data on a part’s repairs and breakdowns. In this way, plant and facilities managers can, in theory, schedule maintenance before failure. If a part typically fails in four years, the maintenance team replaces it in, for example, three years and eleven months.
The benefit of this approach is that unscheduled downtime is avoided. Additionally, by planning maintenance based in advance, you can be sure the required parts are in-house, and you can allocate staff time appropriately.
The limitation of this approach is that it relies on the law of averages. All assets of the same type are created equally. One problem with this is that it is potentially wasteful because you’re replacing a part that might actually have a lot of life left in it. For example, if a specific part happens to be towards the long-lived end of the normal distribution instead of being in the middle. Alternatively, if a specific part happens to be towards the short-lived end of the normal distribution, it would fail if you waited to replace it based on average lifespan.
A better approach than preventive maintenance is predictive maintenance, which helps determine the condition of in-service equipment in order to estimate when maintenance should be performed. This approach promises cost savings over routine or preventive maintenance because tasks are performed only when needed.
Predictive maintenance thus complements the vendor with knowledge about the current state of a part, device, machine, or piece of equipment. LLumin’s READYAsset integrates with control systems and IoT-enabled assets to monitor each machine’s specific state in real-time. Such information can be used to avert problems. For example, based on past experiences, you know that a particular brand of motor is likely to fail within a day if it starts running hotter than normal. Armed with this knowledge, you could immediately repair or replace the item anytime that brand of motor’s temperature spikes.
Proactive maintenance typically is defined as maintenance that takes this type of maintenance to a new level by using analytics to spot trends that might lead to a part’s failure. LLumin READYAsset monitors assets in real-time with expert system and artificial intelligence- (AI-) based rules to anticipate pending failures.
Proactive maintenance is based on an analysis that uses real-time and historical data about an asset to spot trends that might lead to failure. It spots changes and makes inferences about the failure of an asset. Such capabilities can help maintenance staff identify parts or equipment that are likely to fail before their scheduled replacement and maintenance time. When its expert system detects a problem, it triggers corrective action that is based on information derived from collective years of your staff’s knowledge.
With these capabilities, READYAsset eliminates the problems that cause downtime and reduce productivity.