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Author: Tronserve admin

Wednesday 4th August 2021 03:22 PM

Five Types Of Preventative Maintenance In Commercial Facilities


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There are various approaches to preventative maintenance itself, all of these are used to make sure your equipment is performing correctly and prospective problems are distinguished.


Realizing which method of preventative maintenance to use is not always a straightforward decision. Based on the complication and value of your equipment and the possibility of compliance requirements, you might use more than one approach. Below are the five popular 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 in fact practicing time-based maintenance (TBM). Time-based maintenance (TBM) activities might include anything from checking out and cleaning to servicing and part replacements. The relative frequency of TBM is mostly predetermined according to the equipment supplier’s tips and/or past performance of the machine.


TBM has some strengths and cons as a maintenance strategy. It uses lesser 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. For instance, a manufacturer may recommend replacing 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.


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




Failure-finding Maintenance (FFM)


Failure-finding maintenance is executed to be certain 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 extra problems, and shield against damages. Activating an alarm periodically would be viewed failure finding maintenance.


While other types of preventative maintenance involve routinely changing or replacing parts, or noticing an apparent condition that may reveal impending failure, failure-finding maintenance applies to hidden failures that can be uncovered only by actually checking if something still works. By some estimates, up to 40 percent of breakdowns 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 case of elevated cooling water temperature; the functionality of that device will not be discovered without simulating the appropriate conditions and checking if the device gives the right response.


Unfortunately, failure-finding maintenance is normally 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 technique that aims to decrease mechanical failures by evaluating the levels of risk associated with your equipment, and then prioritizing your maintenance activities correctly. The theory behind risk-based maintenance is quite simply Pareto’s Law, which, when applied to maintenance, holds that 80 percent of failures are attributable to just 20 percent of your equipment; hence it makes sense to focus your efforts on those areas.


Both the likelihood of a breakdown and the results of a failure are regarded in support of this approach. In keeping with 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 performed right, risk-based maintenance can optimize both asset performance and your financial resources as well.


Condition-based Monitoring (CBM)


Condition-based monitoring involves monitoring the condition of a piece of operating equipment or machinery to determine what type of maintenance needs to be done and when. Indications of declining performance or imminent failure would signify maintenance needs to be done to restore the machine to its former 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 identifying when a piece of equipment is probably to fail and addressing it before it occurs. Instead of simply aiming to reduce downtime, predictive maintenance aims to maximise uptime. It is an improvement over traditional preventative maintenance approaches because it helps prevent failures in a timely manner.


It is 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 allows 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 affixed 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 show the likelihood of an imminent breakdown.


As an example of this type of preventative maintenance, consider a commercial refrigerated unit. A manufacturer that owns numerous 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 can be stored and investigated using an Internet of Things platform. Using predictive analytics, it is possible to comprehend 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.


Matched with your vital 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 really lessen downtime, decrease your financial expenditure by prolonging the life of your equipment, and enhance the overall safety of your operation.


MANUFACTURING TOMORROW


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Posted on : Wednesday 4th August 2021 03:22 PM

Five Types Of Preventative Maintenance In Commercial Facilities


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Posted by  Tronserve admin
image cap

There are various approaches to preventative maintenance itself, all of these are used to make sure your equipment is performing correctly and prospective problems are distinguished.


Realizing which method of preventative maintenance to use is not always a straightforward decision. Based on the complication and value of your equipment and the possibility of compliance requirements, you might use more than one approach. Below are the five popular 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 in fact practicing time-based maintenance (TBM). Time-based maintenance (TBM) activities might include anything from checking out and cleaning to servicing and part replacements. The relative frequency of TBM is mostly predetermined according to the equipment supplier’s tips and/or past performance of the machine.


TBM has some strengths and cons as a maintenance strategy. It uses lesser 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. For instance, a manufacturer may recommend replacing 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.


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




Failure-finding Maintenance (FFM)


Failure-finding maintenance is executed to be certain 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 extra problems, and shield against damages. Activating an alarm periodically would be viewed failure finding maintenance.


While other types of preventative maintenance involve routinely changing or replacing parts, or noticing an apparent condition that may reveal impending failure, failure-finding maintenance applies to hidden failures that can be uncovered only by actually checking if something still works. By some estimates, up to 40 percent of breakdowns 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 case of elevated cooling water temperature; the functionality of that device will not be discovered without simulating the appropriate conditions and checking if the device gives the right response.


Unfortunately, failure-finding maintenance is normally 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 technique that aims to decrease mechanical failures by evaluating the levels of risk associated with your equipment, and then prioritizing your maintenance activities correctly. The theory behind risk-based maintenance is quite simply Pareto’s Law, which, when applied to maintenance, holds that 80 percent of failures are attributable to just 20 percent of your equipment; hence it makes sense to focus your efforts on those areas.


Both the likelihood of a breakdown and the results of a failure are regarded in support of this approach. In keeping with 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 performed right, risk-based maintenance can optimize both asset performance and your financial resources as well.


Condition-based Monitoring (CBM)


Condition-based monitoring involves monitoring the condition of a piece of operating equipment or machinery to determine what type of maintenance needs to be done and when. Indications of declining performance or imminent failure would signify maintenance needs to be done to restore the machine to its former 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 identifying when a piece of equipment is probably to fail and addressing it before it occurs. Instead of simply aiming to reduce downtime, predictive maintenance aims to maximise uptime. It is an improvement over traditional preventative maintenance approaches because it helps prevent failures in a timely manner.


It is 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 allows 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 affixed 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 show the likelihood of an imminent breakdown.


As an example of this type of preventative maintenance, consider a commercial refrigerated unit. A manufacturer that owns numerous 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 can be stored and investigated using an Internet of Things platform. Using predictive analytics, it is possible to comprehend 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.


Matched with your vital 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 really lessen downtime, decrease your financial expenditure by prolonging the life of your equipment, and enhance the overall safety of your operation.


MANUFACTURING TOMORROW

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industrial 4 industrial iot industrial maintenance