Realizing which method of preventative maintenance to use isn’t always a straightforward decision. Based on the complexity and value of your equipment and the possibility of compliance requirements, you might use more than one approach. Below are the five common types of preventative maintenance in use at commercial facilities today, together with some preventative maintenance examples.

 

Time-based Maintenance (TBM)

 

When you change an air filter once every six months, you're basically doing time-based maintenance (TBM). Time-based maintenance (TBM) activities might involve anything from inspecting and cleaning to servicing and part replacing. The frequence of TBM is customarily predetermined according to the equipment supplier’s ideas and/or past performance of the machine.

 

TBM has some positive aspects and cons as a maintenance strategy. It uses much less manpower than some other maintenance strategies. But even though you’re following the set schedule, in some cases you may be changing or servicing something before it actually requires to be done. For instance, a manufacturer may recommend exchanging a fan filter every three months, but if that filter is located in an area of the building where it isn’t used often, you could go a bit longer without replacing it. That makes the cost of TBM higher than it should be.

 

The next maintenance strategy, condition-based monitoring (discussed below) can help avoid over-maintenance, and is seen as mostly more valuable and economical than TBM.

 

Failure-finding Maintenance (FFM)

 

Failure-finding maintenance is carried out making sure that something - often a protective device of some sort - still works. Protective devices are those designed to call attention to a problem, shutdown a process to avoid more problems, and shield against mishaps. Activating an alarm periodically would be viewed as failure finding maintenance.

 

While other types of preventative maintenance involve routinely changing or replacing parts, or noticing an apparent condition that may well display impending failure, failure-finding maintenance applies to hidden failures that can be discovered only by actually checking if something still works. By some estimates, up to 40 percent of failures in industrial settings fall into the hidden category; and up to 80 percent of those require failure-finding to be rooted out. An example of this type of preventative maintenance: A diesel generator might have a protective device that should turn off the generator in the instance of elevated cooling water temperature; the functionality of that device will not be noticed without simulating the appropriate conditions and checking if the device gives the right response.

 

Unfortunately, failure-finding maintenance is generally given low priority by maintenance professionals, but it is critical to maintaining a safe environment - and sometimes preventing the major disasters that happen resulting from multiple failures.

 

Risk-based Maintenance (RBM)

 

Risk-based maintenance (RBM) is a strategy that aims to lessen mechanical failures by evaluating the levels of risk associated with your equipment, and then prioritizing your maintenance activities as required. The theory behind risk-based maintenance is ultimately Pareto’s Law, which, when applied to maintenance, holds that 80 percent of failures are attributable to just 20 percent of your equipment; this means it makes sense to focus your efforts on those areas.

 

Both the likelihood of a breakdown and the results of a failure are considered in support of this approach. Based upon the results of your evaluation, you can make better decisions about what to inspect, and when. Again and again facility managers do this unconsciously as part of their routines, but it is more effective at delivering results when a methodology is used to help make decisions. When done right, risk-based maintenance can optimize both asset performance and your financial resources as well.

 

Condition-based Monitoring (CBM)

 

Condition-based monitoring involves supervising the condition of a piece of operating equipment or machinery to ascertain what type of maintenance needs to be done and when. Marks of declining performance or imminent failure would suggest maintenance needs to be done to restore the machine to its original level of performance and reliability. This approach is designed to avoid a breakdown by fixing problems before they occur, which means it is a type of predictive maintenance (number 5 below).

 

CBM is a more effective preventative maintenance strategy than time-based, considering that it is a proactive measure intended to specifically identify changes in machine performance and head off issues. Examples of what elements could be monitored to diagnose problems are:

- Visual - This is the most basic form of condition monitoring and may uncover things like cracks or corrosion.

- Vibrations - Changes in the vibrations produced by compressors, pumps, motors and other types of equipment can help spot performance problems.

- Wear debris (tribology) - Analyzing interacting machine surfaces for wear and fractures may serve as an early warning of equipment failure.

- Temperature (thermography) - Corroded electrical connections, faulty machinery, and damaged machine components can all change the temperature distribution of running equipment.

- Sound - The sound of a running machine is usually fairly stable; a change in the noise signal may indicate a change in the condition of the machine.

 

Predictive Maintenance

 

Predictive maintenance is distinguishing when a piece of equipment is probably to fail and addressing it before it occurs. In the place of simply aiming to minimize downtime, predictive maintenance aims to maximize uptime. It’s an improvement over ordinary preventative maintenance approaches because it helps avoid failures in a timely manner.

 

It’s quite similar to condition monitoring in that both strategies have the same goal. The difference is that condition monitoring identifies immediate tasks based on monitoring results, while predictive maintenance enable you plan maintenance tasks based on knowledge about overall equipment health and expected performance - knowledge that comes through the gathering and analysis of data.

 

The Internet of Things makes predictive analytics possible. Sensors installed to your machines and equipment monitor and collect a vast range of operational data, on everything from vibrations, sights, and sounds to temperatures and power consumption. With the help of machine learning and algorithms, this data can then be mined and patterns identified. Eventually, that data can be used to provide valuable insights about aberrant performance that could reveal the likelihood of an imminent breakdown.

 

As an example of this type of preventative maintenance, consider a commercial refrigerated unit. A manufacturer that owns several commercial refrigerated units around the country needs a reliable way to prevent the units from failing because there are high costs associated with failure - including the cost of emergency repairs and product spoilage. As part of a predictive maintenance strategy, the manufacturer could equip each of the refrigerated units with a variety of sensors. The sensors would measure:

- Refrigerator temperature

- Humidity level

- Temperature of the coolant going into and out of the compressor

- Temperature of the coolant going into and out of the evaporator

- Vibration on the compressor

- The number of times the compressor starts and stops

- How long the compressor runs

- The amount of power the compressor is using

 

All this data could be held and evaluated using an Internet of Things platform. Using predictive analytics, it is possible to comprehend the optimal performance of a refrigerator unit and, when defects in the data manifest, to determine if and when the unit might fail. The problem can then be addressed before it happens.

 

Combined with your crucial assets, sensors can give you an unprecedented level of perceptiveness into your daily operations that supports your equipment - and your building - better than preventive maintenance. Predictive maintenance can greatly minimize downtime, decrease your financial expenditure by prolonging the life of your equipment, and increase the overall safety of your operation.

 

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