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Five Types Of Preventative Maintenance In Commercial Facilities

Five Types Of Preventative Maintenance In Commercial Facilities
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There are many approaches to preventative maintenance itself, all of these are used to ensure that your equipment is working correctly and prospective problems are outlined.
 
Realizing which method of preventative maintenance to use isn’t always a straightforward decision. Dependent 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 typical types of preventative maintenance in use at commercial facilities today, in addition to some preventative maintenance examples.
 
Time-based Maintenance (TBM)
 
When you change an air filter once every six months, you are exercising time-based maintenance (TBM). Time-based maintenance (TBM) activities might include anything from checking out and cleaning to servicing and part substitutes. The relative frequency of TBM is customarily predetermined according to the equipment supplier’s tips and/or past performance of the machine.
 
TBM has some advantages and disadvantages as a maintenance strategy. It uses fewer manpower than some other maintenance strategies. But even though you’re following the set schedule, in some cases you may be swapping or servicing something before it actually needs to be done. As 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 is not used often, you could go for a longer time without replacing it. That makes the cost of TBM higher than it should be.
 
Another maintenance strategy, condition-based monitoring (discussed below) can help prevent over-maintenance, and is seen as in general more valuable and economical than TBM.
 
Failure-finding Maintenance (FFM)
 
Failure-finding maintenance is executed to ensure 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 prevent more problems, and protect against accidents. Activating an alarm occasionally would be assumed failure finding maintenance.
 
While other types of preventative maintenance involve routinely changing or replacing parts, or noticing an apparent condition that would probably indicate forthcoming failure, failure-finding maintenance applies to hidden failures that can be unveiled 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 shut down the generator in the event of elevated cooling water temperature; the functionality of that device will not be recognized without simulating the appropriate conditions and checking if the device gives the right response.
 
Unfortunately, failure-finding maintenance is typically given low priority by maintenance professionals, but it is very important 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 method that aims to decrease mechanical failures by evaluating the levels of risk associated with your equipment, and then prioritizing your maintenance activities as necessary. The theory behind risk-based maintenance is virtually Pareto’s Law, which, when applied to maintenance, holds that 80 percent of failures are attributable to just 20 percent of your equipment; this is why it makes sense to focus your efforts on those areas.
 
Both the probability of a breakdown and the results of a failure are regarded in support of this approach. Dependent on the results of your evaluation, you can make better choices about what to inspect, and when. Frequently facility managers do this unconsciously as part of their routines, but it’s more effective at delivering results when a methodology is used to help make decisions. When executed right, risk-based maintenance can optimize both asset performance and your financial resources as well.
 
Condition-based Monitoring (CBM)
 
Condition-based monitoring involves checking the condition of a piece of operating equipment or machinery to identify what type of maintenance needs to be done and when. Problems of decreasing performance or imminent failure would reveal maintenance needs to be done to restore the machine to its previous 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, simply because it is a proactive measure intended to particularly 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 identifying when a piece of equipment is inclined to fail and addressing it before it happens. Instead of simply aiming to minmise downtime, predictive maintenance aims to maximise uptime. It’s an improvement over regular preventative maintenance approaches because it helps reduce failures in a timely manner.
 
It’s very equivalent 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 helps 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 fixed 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 demonstrate the likelihood of an imminent breakdown.
 
As an example of this type of preventative maintenance, consider a commercial refrigerated unit. A manufacturer that owns a large number of commercial refrigerated units around the country needs a reputable 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 placed and examined using an Internet of Things platform. Using predictive analytics, it is possible to understand the optimal performance of a refrigerator unit and, when anomalies in the data happen, to determine if and when the unit might fail. The problem can then be addressed before it happens.
 
Coupled with your crucial assets, sensors can give you an unprecedented level of understanding 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 improve the overall safety of your operation.
 

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